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Two-particle azimuthal correlations are measured with the ALICE apparatus in pp collisions at s√=13 TeV to explore strangeness- and multiplicity-related effects in the fragmentation of jets and the transition regime between bulk and hard production, probed with the condition that a strange meson (K0S) or baryon (Λ) with transverse momentum pT>3 GeV/c is produced. Azimuthal correlations between kaons or Λ hyperons with other hadrons are presented at midrapidity for a broad range of the trigger (3<ptriggT<20 GeV/c) and associated particle pT (1 GeV/c <passocT<ptriggT), for minimum-bias events and as a function of the event multiplicity. The near- and away-side peak yields are compared for the case of either K0S or Λ(Λ¯¯¯¯) being the trigger particle with that of inclusive hadrons (a sample dominated by pions). In addition, the measurements are compared with predictions from PYTHIA 8 and EPOS LHC event generators.
Charmonium production in pp collisions at center-of-mass energy of s√ = 13 TeV and p-Pb collisions at center-of-mass energy per nucleon pair of sNN−−−√ = 8.16 TeV is studied as a function of charged-particle pseudorapidity density with ALICE. Ground and excited charmonium states (J/ψ, ψ(2S)) are measured from their dimuon decays in the interval of rapidity in the center-of-mass frame 2.5<ycms<4.0 for pp collisions, and 2.03<ycms<3.53 and −4.46<ycms<−2.96 for p-Pb collisions. The charged-particle pseudorapidity density is measured around midrapidity (|η|<1.0). In pp collisions, the measured charged-particle multiplicity extends to about six times the average value, while in p-Pb collisions at forward (backward) rapidity a multiplicity corresponding to about three (four) times the average is reached. The ψ(2S) yield increases with the charged-particle pseudorapidity density. The ratio of ψ(2S) over J/ψ yield does not show a significant multiplicity dependence in either colliding system, suggesting a similar behavior of J/ψ and ψ(2S) yields with respect to charged-particle pseudorapidity density. The results are also compared with model calculations.
We present the first systematic comparison of the charged-particle pseudorapidity densities for three widely different collision systems, pp, p-Pb, and Pb-Pb, at the top energy of the Large Hadron Collider (sNN−−−√=5.02 TeV) measured over a wide pseudorapidity range (−3.5<η<5), the widest possible among the four experiments at that facility. The systematic uncertainties are minimised since the measurements are recorded by the same experimental apparatus (ALICE). The distributions for p-Pb and Pb-Pb collisions are determined as a function of the centrality of the collisions, while results from pp collisions are reported for inelastic events with at least one charged particle at midrapidity. The charged-particle pseudorapidity densities are, under simple and robust assumptions, transformed to charged-particle rapidity densities. This allows for the calculation and the presentation of the evolution of the width of the rapidity distributions and of a lower bound on the Bjorken energy density, as a function of the number of participants in all three collision systems. We find a decreasing width of the particle production, and roughly a smooth ten fold increase in the energy density, as the system size grows, which is consistent with a gradually higher dense phase of matter.
The production of Λ baryons and K0S mesons (V0 particles) was measured in p-Pb collisions at sNN−−−√=5.02 TeV and pp collisions at s√=7 TeV with ALICE at the LHC. The production of these strange particles is studied separately for particles associated with hard scatterings and the underlying event to shed light on the baryon-to-meson ratio enhancement observed at intermediate transverse momentum (pT) in high multiplicity pp and p-Pb collisions. Hard scatterings are selected on an event-by-event basis with jets reconstructed with the anti-kT algorithm using charged particles. The production of strange particles associated with jets pchT,jet>10 and pchT,jet>20 GeV/c in p-Pb collisions, and with jet pchT,jet>10 GeV/c in pp collisions is reported as a function of pT. Its dependence on angular distance from the jet axis, R(V0,jet), for jets with pchT,jet>10 GeV/c in p-Pb collisions is reported as well. The pT-differential production spectra of strange particles associated with jets are found to be harder compared to that in the underlying event and both differ from the inclusive measurements. In events containing a jet, the density of the V0 particles in the underlying event is found to be larger than the density in the minimum bias events. The Λ/K0S ratio associated with jets in p-Pb collisions is consistent with the ratio in pp collisions and follows the expectation of jets fragmenting in vacuum. On the other hand, this ratio within jets is consistently lower than the one obtained in the underlying event and it does not show the characteristic enhancement of baryons at intermediate pT often referred to as "baryon anomaly" in the inclusive measurements.
The production of Λ baryons and K0S mesons (V0 particles) was measured in p-Pb collisions at sNN−−−√=5.02 TeV and pp collisions at s√=7 TeV with ALICE at the LHC. The production of these strange particles is studied separately for particles associated with hard scatterings and the underlying event to shed light on the baryon-to-meson ratio enhancement observed at intermediate transverse momentum (pT) in high multiplicity pp and p-Pb collisions. Hard scatterings are selected on an event-by-event basis with jets reconstructed with the anti-kT algorithm using charged particles. The production of strange particles associated with jets pchT,jet>10 and pchT,jet>20 GeV/c in p-Pb collisions, and with jet pchT,jet>10 GeV/c in pp collisions is reported as a function of pT. Its dependence on angular distance from the jet axis, R(V0,jet), for jets with pchT,jet>10 GeV/c in p-Pb collisions is reported as well. The pT-differential production spectra of strange particles associated with jets are found to be harder compared to that in the underlying event and both differ from the inclusive measurements. In events containing a jet, the density of the V0 particles in the underlying event is found to be larger than the density in the minimum bias events. The Λ/K0S ratio associated with jets in p-Pb collisions is consistent with the ratio in pp collisions and follows the expectation of jets fragmenting in vacuum. On the other hand, this ratio within jets is consistently lower than the one obtained in the underlying event and it does not show the characteristic enhancement of baryons at intermediate pT often referred to as "baryon anomaly" in the inclusive measurements.
The measurement of the production of f0(980) in inelastic pp collisions at s√=5.02 TeV is presented. This is the first reported measurement of inclusive f0(980) production at LHC energies. The production is measured at midrapidity, |y|<0.5, in a wide transverse momentum range, 0<pT<16 GeV/c, by reconstructing the resonance in the f0(980)→π+π− hadronic decay channel using the ALICE detector. The pT-differential yields are compared to those of pions, protons and ϕ mesons as well as to predictions from the HERWIG 7.2 QCD-inspired Monte Carlo event generator and calculations from a coalescence model that uses the AMPT model as an input. The ratio of the pT-integrated yield of f0(980) relative to pions is compared to measurements in e+e− and pp collisions at lower energies and predictions from statistical hadronisation models and HERWIG 7.2. A mild collision energy dependence of the f0(980) to pion production is observed in pp collisions from SPS to LHC energies. All considered models underpredict the pT-integrated f0(980)/(π++π−) ratio. The prediction from the γs-CSM model assuming a zero total strangeness content of f0(980) is consistent with the data within 1.9σ and is the closest to the data. The results provide an essential reference for future measurements of the particle yield and nuclear modification in p−Pb and Pb−Pb collisions, which have been proposed to be instrumental to probe the elusive nature and quark composition of the f0(980) scalar meson.
First measurements of balance functions (BFs) of all combinations of identified charged hadron (π,K,p) pairs in Pb−Pb collisions at sNN−−−√=2.76 TeV recorded by the ALICE detector are presented. The BF measurements are carried out as two-dimensional differential correlators versus the relative rapidity (Δy) and azimuthal angle (Δφ) of hadron pairs, and studied as a function of collision centrality. The Δφ dependence of BFs is expected to be sensitive to the light quark diffusivity in the quark−gluon plasma. While the BF azimuthal widths of all pairs substantially decrease from peripheral to central collisions, the longitudinal widths exhibit mixed behaviors: BFs of ππ and cross-species pairs narrow significantly in more central collisions, whereas those of KK and pp are found to be independent of collision centrality. This dichotomy is qualitatively consistent with the presence of strong radial flow effects and the existence of two stages of quark production in relativistic heavy-ion collisions. Finally, the first measurements of the collision centrality evolution of BF integrals are presented, with the observation that charge balancing fractions are nearly independent of collision centrality in Pb−Pb collisions. Overall, the results presented provide new and challenging constraints for theoretical models of hadron production and transport in relativistic heavy-ion collisions.
The jet angularities are a class of jet substructure observables which characterize the angular and momentum distribution of particles within jets. These observables are sensitive to momentum scales ranging from perturbative hard scatterings to nonperturbative fragmentation into final-state hadrons. We report measurements of several groomed and ungroomed jet angularities in pp collisions at s√=5.02 TeV with the ALICE detector. Jets are reconstructed using charged particle tracks at midrapidity (|η|<0.9). The anti-kT algorithm is used with jet resolution parameters R=0.2 and R=0.4 for several transverse momentum pch jetT intervals in the 20−100 GeV/c range. Using the jet grooming algorithm Soft Drop, the sensitivity to softer, wide-angle processes, as well as the underlying event, can be reduced in a way which is well-controlled in theoretical calculations. We report the ungroomed jet angularities, λα, and groomed jet angularities, λα,g, to investigate the interplay between perturbative and nonperturbative effects at low jet momenta. Various angular exponent parameters α=1, 1.5, 2, and 3 are used to systematically vary the sensitivity of the observable to collinear and soft radiation. Results are compared to analytical predictions at next-to-leading-logarithmic accuracy, which provide a generally good description of the data in the perturbative regime but exhibit discrepancies in the nonperturbative regime. Moreover, these measurements serve as a baseline for future ones in heavy-ion collisions by providing new insight into the interplay between perturbative and nonperturbative effects in the angular and momentum substructure of jets. They supply crucial guidance on the selection of jet resolution parameter, jet transverse momentum, and angular scaling variable for jet quenching studies.
The very forward energy is a powerful tool for characterising the proton fragmentation in pp and p-Pb collisions and, studied in correlation with particle production at midrapidity, provides direct insightsinto the initial stages and the subsequent evolution of the collision. Furthermore, the correlation between the forward energy and the production of particles with large transverse momenta at midrapidity provides information complementary to the measurements of the underlying event, which are usually interpreted in the framework of models implementing centrality-dependent multiple parton interaction. Results about the very forward energy, measured by the ALICE zero degree calorimeters (ZDC), and its dependence on the activity measured at midrapidity in pp collisions at s√=13 TeV and in p-Pb collisions at sNN−−−√=8.16 TeV are presented and discussed. The measurements performed in pp collisions are compared with the expectations of three hadronic interaction event generators: PYTHIA 6 (Perugia 2011 tune), PYTHIA 8 (Monash tune), and EPOS LHC. These results provide new constraints on the validity of models in describing the beam remnants at very forward rapidities, where perturbative QCD cannot be used.
The production of J/ψ is measured at midrapidity (|y|<0.9) in proton-proton collisions at s√ = 5.02 and 13 TeV, through the dielectron decay channel, using the ALICE detector at the Large Hadron Collider. The data sets used for the analyses correspond to integrated luminosities of Lint = 19.4 ± 0.4 nb−1 and Lint = 32.2 ± 0.5 nb−1 at s√ = 5.02 and 13 TeV, respectively. The fraction of non-prompt J/ψ mesons, i.e. those originating from the decay of beauty hadrons, is measured down to a transverse momentum pT = 2 GeV/c (1 GeV/c) at s√ = 5.02 TeV (13 TeV). The pT and rapidity (y) differential cross sections, as well as the corresponding values integrated over pT and y, are carried out separately for prompt and non-prompt J/ψ mesons. The results are compared with measurements from other experiments and theoretical calculations based on quantum chromodynamics (QCD). The shapes of the pT and y distributions of beauty quarks predicted by state-of-the-art perturbative QCD models are used to extrapolate an estimate of the bb¯¯¯ pair cross section at midrapidity and in the total phase space. The total bb¯¯¯ cross sections are found to be σbb¯¯¯=541±45(stat.)±69(syst.)+10−12(extr.) μb and σbb¯¯¯ = 218±37(stat.)±31(syst.)+8.2−9.1(extr.) μb at s√ = 13 and 5.02 TeV, respectively. The value obtained from the combination of ALICE and LHCb measurements in pp collisions at s√ = 13 TeV is also provided.
We report on the inclusive J/ψ production cross section measured at the CERN Large Hadron Collider in proton-proton collisions at a centre-of-mass energy s√ = 13 TeV. The J/ψ mesons are reconstructed in the e+e− decay channel and the measurements are performed at midrapidity (|y|<0.9) in the transverse-momentum interval 0<pT<40 GeV/c, using a minimum-bias data sample corresponding to an integrated luminosity Lint=32.2 nb−1 and an Electromagnetic Calorimeter triggered data sample with Lint=8.3 pb−1. The pT-integrated J/ψ production cross section at midrapidity, computed using the minimum-bias data sample, is dσ/dy|y=0=8.97±0.24 (stat)±0.48 (syst)±0.15 (lumi) μb. An approximate logarithmic dependence with the collision energy is suggested by these results and available world data, in agreement with model predictions. The integrated and pT-differential measurements are compared with measurements in pp collisions at lower energies and with several recent phenomenological calculations based on the non-relativistic QCD and Color Evaporation models.
The production yield and angular anisotropy of prompt D+s mesons were measured as a function of transverse momentum (pT) in Pb-Pb collisions at a centre-of-mass energy per nucleon pair sNN−−−−√=5.02 TeV collected with the ALICE detector at the LHC. D+s mesons and their charge conjugates were reconstructed at midrapidity (|y|<0.5) from their hadronic decay channel D+s→ϕπ+, with ϕ→K−K+, in the pT intervals 2<pT<50 GeV/c and 2<pT<36 GeV/c for the 0-10% and 30-50% centrality intervals. For pT>10 GeV/c, the measured D+s-meson nuclear modification factor RAA is consistent with the one of non-strange D mesons within uncertainties, while at lower pT a hint for a D+s-meson RAA larger than that of non-strange D mesons is seen. The enhanced production of D+s relative to non-strange D mesons is also studied by comparing the pT-dependent D+s/D0 production yield ratios in Pb-Pb and in pp collisions. The ratio measured in Pb-Pb collisions is found to be on average higher than that in pp collisions in the interval 2<pT<8 GeV/c with a significance of 2.3σ and 2.4σ for the 0-10% and 30-50% centrality intervals. The azimuthal anisotropy coefficient v2 of prompt D+s mesons was measured in Pb-Pb collisions in the 30-50% centrality interval and is found to be compatible with that of non-strange D mesons. The main features of the measured RAA, D+s/D0 ratio, and v2 as a function of pT are described by theoretical calculations of charm-quark transport in a hydrodynamically expanding quark-gluon plasma including hadronisation via charm-quark recombination with light quarks from the medium. The pT-integrated production yield of D+s mesons is compatible with the prediction of the statistical hadronisation model.
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.
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 production of ϕ mesons has been studied in pp collisions at LHC energies with the ALICE detector via the dimuon decay channel in the rapidity region 2.5<y<4. Measurements of the differential cross section d2σ/dydpT are presented as a function of the transverse momentum (pT) at the center-of-mass energies s√=5.02, 8 and 13 TeV and compared with the ALICE results at midrapidity. The differential cross sections at s√=5.02 and 13 TeV are also studied in several rapidity intervals as a function of pT, and as a function of rapidity in three pT intervals. A hardening of the pT-differential cross section with the collision energy is observed, while, for a given energy, pT spectra soften with increasing rapidity and, conversely, rapidity distributions get slightly narrower at increasing pT. The new results, complementing the published measurements at s√=2.76 and 7 TeV, allow one to establish the energy dependence of ϕ meson production and to compare the measured cross sections with phenomenological models. None of the considered models manages to describe the evolution of the cross section with pT and rapidity at all the energies.
A measurement of the inclusive b-jet production cross section is presented in pp and p-Pb collisions at sNN−−−√=5.02 TeV, using data collected with the ALICE detector at the LHC. The jets were reconstructed in the central rapidity region |η|<0.5 from charged particles using the anti-kT algorithm with resolution parameter R=0.4. Identification of b jets exploits the long lifetime of b hadrons, using the properties of secondary vertices and impact parameter distributions. The pT-differential inclusive production cross section of b jets, as well as the corresponding inclusive b-jet fraction, are reported for pp and p-Pb collisions in the jet transverse momentum range 10≤pT, ch jet≤100 GeV/c, together with the nuclear modification factor, Rb-jetpPb. The analysis thus extends the lower pT limit of b-jet measurements at the LHC. The nuclear modification factor is found to be consistent with unity, indicating that the production of b jets in p-Pb at sNN−−−√=5.02 TeV is not affected by cold nuclear matter effects within the current precision. The measurements are well reproduced by POWHEG NLO pQCD calculations with PYTHIA fragmentation.
The study of nuclei and antinuclei production has proven to be a powerful tool to investigate the formation mechanism of loosely bound states in high-energy hadronic collisions. The first measurement of the production of 3ΛH in p-Pb collisions at sNN−−−√ = 5.02 TeV is presented in this Letter. Its production yield measured in the rapidity interval −1<y<0 for the 40% highest multiplicity p-Pb collisions is dN/dy=[6.3±1.8(stat.)±1.2(syst.)]×10−7. The measurement is compared with the expectations of statistical hadronisation and coalescence models, which describe the nucleosynthesis in hadronic collisions. These two models predict very different yields of the hypertriton in charged particle multiplicity environments relevant to small collision systems such as p-Pb and therefore the measurement of dN/dy is crucial to distinguish between them. The precision of this measurement leads to the exclusion with a significance larger than 6.9σ of some configurations of the statistical hadronization model, thus constraining the theory behind the production of loosely bound states at hadron colliders.
The transverse-momentum (pT) spectra and coalescence parameters B2 of (anti)deuterons are measured in pp collisions at s√=13 TeV in and out of jets. In this measurement, the direction of the leading particle with the highest pT in the event (pleadT>5 GeV/c) is used as an approximation for the jet axis. The event is consequently divided into three azimuthal regions and the jet signal is obtained as the difference between the Toward region, that contains jet fragmentation products in addition to the underlying event (UE), and the Transverse region, which is dominated by the UE. The coalescence parameter in the jet is found to be approximately a factor of 10 larger than that in the underlying event. This experimental observation is consistent with the coalescence picture and can be attributed to the smaller average phase-space distance between nucleons inside the jet cone as compared to the underlying event. The results presented in this Letter are compared to predictions from a simple nucleon coalescence model, where the phase space distributions of nucleons are generated using PYTHIA 8 with the Monash 2013 tuning, and to predictions from a deuteron production model based on ordinary nuclear reactions with parametrized energy-dependent cross sections tuned on data. The latter model is implemented in PYTHIA 8.3. Both models reproduce the observed large difference between in-jet and out-of-jet coalescence parameters.
Femtoscopic correlations with the particle pair combinations K0SK0S and K0SK± are studied in pp collisions at s√=5.02 and 13 TeV by the ALICE experiment. At both energies, boson source parameters are extracted for both pair combinations, by fitting models based on Gaussian size distributions of the sources, to the measured two-particle correlation functions. The interaction model used for the K0SK0S analysis includes quantum statistics and strong final-state interactions through the f0(980) and a0(980) resonances. The model used for the K0SK± analysis includes only the final-state interaction through the a0 resonance. Source parameters extracted in the present work are compared with published values from pp collisions at s√= 7 TeV and the different pair combinations are found to be consistent. From the observation that the strength of the K0SK0S correlations is significantly greater than the strength of the K0SK± correlations, the new results are compatible with the a0 resonance being a tetraquark state of the form (q1,q2¯¯¯¯¯,s,s¯¯¯), where q1 and q2 are u or d quarks.
Angular correlations of heavy-flavour and charged particles in high-energy proton-proton collisions are sensitive to the production mechanisms of heavy quarks and to their fragmentation as well as hadronisation processes. The measurement of the azimuthal-correlation function of prompt D mesons with charged particles in proton-proton collisions at a centre-of-mass energy of s√=13 TeV with the ALICE detector is reported, considering D0, D+, and D∗+ mesons in the transverse-momentum interval 3<pT<36 GeV/c at midrapidity (|y|<0.5), and charged particles with pT>0.3 GeV/c and pseudorapidity |η|<0.8. This measurement has an improved precision and provides an extended transverse-momentum coverage compared to previous ALICE measurements at lower energies. The study is also performed as a function of the charged-particle multiplicity, showing no modifications of the correlation function with multiplicity within uncertainties. The properties and the transverse-momentum evolution of the near- and away-side correlation peaks are studied and compared with predictions from various Monte Carlo event generators. Among those considered, PYTHIA8 and POWHEG+PYTHIA8 provide the best description of the measured observables. The obtained results can provide guidance on tuning the generators.
This article presents groomed jet substructure measurements in pp and Pb−Pb collisions at sNN−−−√=5.02 TeV with the ALICE detector. The Soft Drop grooming algorithm provides access to the hard parton splittings inside a jet by removing soft wide-angle radiation. We report the groomed jet momentum splitting fraction, zg, and the (scaled) groomed jet radius, θg. Charged-particle jets are reconstructed at midrapidity using the anti-kT algorithm with resolution parameters R=0.2 and R=0.4. In heavy-ion collisions, the large underlying event poses a challenge for the reconstruction of groomed jet observables, since fluctuations in the background can cause groomed parton splittings to be misidentified. By using strong grooming conditions to reduce this background, we report these observables fully corrected for detector effects and background fluctuations for the first time. A narrowing of the θg distribution in Pb−Pb collisions compared to pp collisions is seen, which provides direct evidence of the modification of the angular structure of jets in the quark−gluon plasma. No significant modification of the zg distribution in Pb−Pb collisions compared to pp collisions is observed. These results are compared with a variety of theoretical models of jet quenching, and provide constraints on jet energy-loss mechanisms and coherence effects in the quark−gluon plasma.
Fluctuation measurements are important sources of information on the mechanism of particle production at LHC energies. This article reports the first experimental results on third-order cumulants of the net-proton distributions in Pb−Pb collisions at a center-of-mass energy sNN−−−√=5.02 TeV recorded by the ALICE detector. The results on the second-order cumulants of net-proton distributions at sNN−−−√=2.76 and 5.02 TeV are also discussed in view of effects due to the global and local baryon number conservation. The results demonstrate the presence of long-range rapidity correlations between protons and antiprotons. Such correlations originate from the early phase of the collision. The experimental results are compared with HIJING and EPOS model calculations, and the dependence of the fluctuation measurements on the phase-space coverage is examined in the context of lattice quantum chromodynamics (LQCD) and hadron resonance gas (HRG) model estimations. The measured third-order cumulants are consistent with zero within experimental uncertainties of about 4% and are described well by LQCD and HRG predictions.
The study of the azimuthal anisotropy of inclusive muons produced in p-Pb collisions at sNN−−−√=8.16 TeV, using the ALICE detector at the LHC is reported. The measurement of the second-order Fourier coefficient of the particle azimuthal distribution, v2, is performed as a function of transverse momentum pT in the 0-20% high-multiplicity interval at both forward (2.03<yCMS<3.53) and backward (−4.46<yCMS<−2.96) rapidities over a wide pT range, 0.5<pT<10 GeV/c, in which a dominant contribution of muons from heavy-flavour hadron decays is expected at pT>2 GeV/c. The v2 coefficient of inclusive muons is extracted using two different techniques, namely two-particle cumulants, used for the first time for heavy-flavour measurements, and forward-central two-particle correlations. Both techniques give compatible results. A positive v2 is measured at both forward and backward rapidities with a significance larger than 4.7σ and 7.6σ, respectively, in the interval 2<pT<6 GeV/c. Comparisons with previous measurements in p-Pb collisions at sNN−−−√=5.02 TeV, and with AMPT and CGC-based theoretical calculations are discussed. The findings impose new constraints on the theoretical interpretations of the origin of the collective behaviour in small collision systems.
The study of the azimuthal anisotropy of inclusive muons produced in p-Pb collisions at sNN−−−√=8.16 TeV, using the ALICE detector at the LHC is reported. The measurement of the second-order Fourier coefficient of the particle azimuthal distribution, v2, is performed as a function of transverse momentum pT in the 0-20% high-multiplicity interval at both forward (2.03<yCMS<3.53) and backward (−4.46<yCMS<−2.96) rapidities over a wide pT range, 0.5<pT<10 GeV/c, in which a dominant contribution of muons from heavy-flavour hadron decays is expected at pT>2 GeV/c. The v2 coefficient of inclusive muons is extracted using two different techniques, namely two-particle cumulants, used for the first time for heavy-flavour measurements, and forward-central two-particle correlations. Both techniques give compatible results. A positive v2 is measured at both forward and backward rapidities with a significance larger than 4.7σ and 7.6σ, respectively, in the interval 2<pT<6 GeV/c. Comparisons with previous measurements in p-Pb collisions at sNN−−−√=5.02 TeV, and with AMPT and CGC-based theoretical calculations are discussed. The findings impose new constraints on the theoretical interpretations of the origin of the collective behaviour in small collision systems.
The multiplicity dependence of jet production in pp collisions at the centre-of-mass energy of s√=13 TeV is studied for the first time. Jets are reconstructed from charged particles using the anti-kT algorithm with resolution parameters R varying from 0.2 to 0.7. The jets are measured in the pseudorapidity range |ηjet|<0.9−R and in the transverse momentum range 5<pchT,jet<140 GeV/c. The multiplicity intervals are categorised by the ALICE forward detector V0. The pT differential cross section of charged-particle jets are compared to leading order (LO) and next-to-leading order (NLO) perturbative quantum chromodynamics (pQCD) calculations. It is found that the data are better described by the NLO calculation, although the NLO prediction overestimates the jet cross section below 20 GeV/c. The cross section ratios for different R are also measured and compared to model calculations. These measurements provide insights into the angular dependence of jet fragmentation. The jet yield increases with increasing self-normalised charged-particle multiplicity. This increase shows only a weak dependence on jet transverse momentum and resolution parameter at the highest multiplicity. While such behaviour is qualitatively described by the present version of PYTHIA, quantitative description may require implementing new mechanisms for multi-particle production in hadronic collisions.
The multiplicity dependence of jet production in pp collisions at the centre-of-mass energy of s√=13 TeV is studied for the first time. Jets are reconstructed from charged particles using the anti-kT algorithm with resolution parameters R varying from 0.2 to 0.7. The jets are measured in the pseudorapidity range |ηjet|<0.9−R and in the transverse momentum range 5<pchT,jet<140 GeV/c. The multiplicity intervals are categorised by the ALICE forward detector V0. The pT differential cross section of charged-particle jets are compared to leading order (LO) and next-to-leading order (NLO) perturbative quantum chromodynamics (pQCD) calculations. It is found that the data are better described by the NLO calculation, although the NLO prediction overestimates the jet cross section below 20 GeV/c. The cross section ratios for different R are also measured and compared to model calculations. These measurements provide insights into the angular dependence of jet fragmentation. The jet yield increases with increasing self-normalised charged-particle multiplicity. This increase shows only a weak dependence on jet transverse momentum and resolution parameter at the highest multiplicity. While such behaviour is qualitatively described by the present version of PYTHIA, quantitative description may require implementing new mechanisms for multi-particle production in hadronic collisions.
This article presents the first measurement of the interaction between charm hadrons and nucleons. The two-particle momentum correlations of pD− and p¯¯¯D+ pairs are measured by the ALICE Collaboration in high-multiplicity pp collisions at s√=13 TeV. The data are compatible with the Coulomb-only interaction hypothesis within (1.1-1.5)σ. The level of agreement slightly improves if an attractive nucleon(N)D¯¯¯¯ strong interaction is considered, in contrast to most model predictions which suggest an overall repulsive interaction. This measurement allows for the first time an estimation of the 68% confidence level interval for the isospin I=0 inverse scattering length of the ND¯¯¯¯ state f−10, I=0∈[−0.4,0.9] fm−1, assuming negligible interaction for the isospin I=1 channel.
This Letter presents the first measurement of the interaction between charm hadrons and nucleons. The two-particle momentum correlations of pD− and p¯¯¯D+ pairs are measured by the ALICE Collaboration in high-multiplicity pp collisions at s√=13 TeV. The data are compatible with the Coulomb-only interaction hypothesis within (1.1-1.5)σ. Considering an attractive nucleon(N)D¯¯¯¯ strong interaction, in contrast to most model predictions which suggest an overall repulsive interaction, slightly improves the level of agreement. This measurement allows for the first time an estimation of the 68% confidence level interval for the isospin I=0 inverse scattering length of the ND¯¯¯¯ state f−10, I=0∈[−0.4,0.9] fm−1, assuming negligible interaction for the isospin I=1 channel.
We present the first measurement of event-by-event fluctuations in the kaon sector in Pb-Pb collisions at sNN−−−√= 2.76 TeV with the ALICE detector at the LHC. The robust fluctuation correlator νdyn is used to evaluate the magnitude of fluctuations of the relative yields of neutral and charged kaons, as well as the relative yields of charged kaons, as a function of collision centrality and selected kinematic ranges. While the correlator νdyn[K+,K−] exhibits a scaling approximately in inverse proportion of the charged particle multiplicity, νdyn[K0S,K±] features a significant deviation from such scaling. Within uncertainties, the value of νdyn[K0S,K±] is independent of the selected transverse momentum interval, while it exhibits a pseudorapidity dependence. The results are compared with HIJING, AMPT and EPOS-LHC predictions, and are further discussed in the context of the possible production of disoriented chiral condensates in central Pb-Pb collisions.
The pseudorapidity density of charged particles with minimum transverse momentum (pT) thresholds of 0.15, 0.5, 1, and 2 GeV/c was measured in pp collisions at centre-of-mass energies of √s = 5.02 and 13 TeV with the ALICE detector. The study is carried out for inelastic collisions with at least one primary charged particle having a pseudorapidity (η) within ±0.8 and pT larger than the corresponding threshold. The measurements were also performed for inelastic and non-single-diffractive events as well as for inelastic events with at least one charged particle having |η| < 1 in pp collisions at √s = 5.02 TeV for the first time at the LHC. The measurements are compared to the PYTHIA 6, PYTHIA 8, and EPOS-LHC models. In general, the models describe the pseudorapidity dependence of particle production well, however, discrepancies are observed for event classes including diffractive events and for the highest transverse momentum threshold (pT > 2 GeV/c), highlighting the importance of such measurements for tuning event generators. The new measurements agree within uncertainties with results from the ATLAS and CMS experiments.
Antimatter particles such as positrons and antiprotons abound in the cosmos. Much less common are light antinuclei, composed of antiprotons and antineutrons, which can be produced in our galaxy via high-energy cosmic-ray collisions with the interstellar medium or could also originate from the annihilation of the still undiscovered dark-matter particles. On Earth, the only way to produce and study antinuclei with high precision is to create them at high-energy particle accelerators like the Large Hadron Collider (LHC). Though the properties of elementary antiparticles have been studied in detail, knowledge of the interaction of light antinuclei with matter is rather limited. This work focuses on the determination of the disappearance probability of \ahe\ when it encounters matter particles and annihilates or disintegrates. The material of the ALICE detector at the LHC serves as a target to extract the inelastic cross section for \ahe\ in the momentum range of 1.17≤p<10 GeV/c. This inelastic cross section is measured for the first time and is used as an essential input to calculations of the transparency of our galaxy to the propagation of 3He¯¯¯¯¯¯ stemming from dark-matter decays and cosmic-ray interactions within the interstellar medium. A transparency of about 50% is estimated using the GALPROP program for a specific dark-matter profile and a standard set of propagation parameters. For cosmic-ray sources, the obtained transparency with the same propagation scheme varies with increasing 3He¯¯¯¯¯¯ momentum from 25% to 90%. The absolute uncertainties associated to the 3He¯¯¯¯¯¯ inelastic cross section measurements are of the order of 10%−15%. The reported results indicate that 3He¯¯¯¯¯¯ nuclei can travel long distances in the galaxy, and can be used to study cosmic-ray interactions and dark-matter decays.
In our Galaxy, light antinuclei composed of antiprotons and antineutrons can be produced through high-energy cosmic-ray collisions with the interstellar medium or could also originate from the annihilation of dark-matter particles that have not yet been discovered. On Earth, the only way to produce and study antinuclei with high precision is to create them at high-energy particle accelerators. Although the properties of elementary antiparticles have been studied in detail, the knowledge of the interaction of light antinuclei with matter is limited. We determine the disappearance probability of 3He¯¯¯¯¯¯ when it encounters matter particles and annihilates or disintegrates within the ALICE detector at the Large Hadron Collider. We extract the inelastic interaction cross section, which is then used as input to calculations of the transparency of our Galaxy to the propagation of 3He¯¯¯¯¯¯ stemming from dark-matter annihilation and cosmic-ray interactions within the interstellar medium. For a specific dark-matter profile, we estimate a transparency of about 50%, whereas it varies with increasing 3He¯¯¯¯¯¯ momentum from 25% to 90% for cosmic-ray sources. The results indicate that 3He¯¯¯¯¯¯ nuclei can travel long distances in the Galaxy, and can be used to study cosmic-ray interactions and dark-matter annihilation.
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.
The ALICE Collaboration reports the first fully-corrected measurements of the N-subjettiness observable for track-based jets in heavy-ion collisions. This study is performed using data recorded in pp and Pb−Pb collisions at centre-of-mass energies of √s=7 TeV and √sNN=2.76\,TeV, respectively. In particular the ratio of 2-subjettiness to 1-subjettiness, τ2/τ1, which is sensitive to the rate of two-pronged jet substructure, is presented. Energy loss of jets traversing the strongly interacting medium in heavy-ion collisions is expected to change the rate of two-pronged substructure relative to vacuum. The results are presented for jets with a resolution parameter of R=0.4 and charged jet transverse momentum of 40≤pT,jet≤60 GeV/c, which constitute a larger jet resolution and lower jet transverse momentum interval than previous measurements in heavy-ion collisions. This has been achieved by utilising a semi-inclusive hadron-jet coincidence technique to suppress the larger jet combinatorial background in this kinematic region. No significant modification of the τ2/τ1 observable for track-based jets in Pb--Pb collisions is observed relative to vacuum PYTHIA6 and PYTHIA8 references at the same collision energy. The measurements of τ2/τ1, together with the splitting aperture angle ΔR, are also performed in pp collisions at √s=7 TeV for inclusive jets. These results are compared with PYTHIA calculations at √s=7 TeV, in order to validate the model as a vacuum reference for the Pb−Pb centre-of-mass energy. The PYTHIA references for τ2/τ1 are shifted to larger values compared to the measurement in pp collisions. This hints at a reduction in the rate of two-pronged jets in Pb--Pb collisions compared to pp collisions.
Understanding the production mechanism of light (anti)nuclei is one of the key challenges of nuclear physics and has important consequences for astrophysics, since it provides an input for indirect dark-matter searches in space. In this paper, the latest results about the production of light (anti)nuclei in pp collisions at s√=13 TeV are presented, focusing on the comparison with the predictions of coalescence and thermal models. For the first time, the coalescence parameters B2 for deuterons and B3 for helions are compared with parameter-free theoretical predictions that are directly constrained by the femtoscopic measurement of the source radius in the same event class. A fair description of the data with a Gaussian wave function is observed for both deuteron and helion, supporting the coalescence mechanism for the production of light (anti)nuclei in pp collisions. This method paves the way for future investigations of the internal structure of more complex nuclear clusters, including the hypertriton.
Background: Driven by globalization, urbanization and climate change, the distribution range of invasive vector species has expanded to previously colder ecoregions. To reduce health-threatening impacts on humans, insect vectors are extensively studied. Population genomics can reveal the genomic basis of adaptation and help to identify emerging trends of vector expansion.
Results: By applying whole genome analyses and genotype-environment associations to populations of the main dengue vector Ae. aegypti, sampled along an altitudinal temperature gradient in Nepal (200- 1300m), we identify adaptive traits and describe the species’ genomic footprint of climate adaptation to colder ecoregions. We found two clusters of differentiation with significantly different allele frequencies in genes associated to climate adaptation between the highland population (1300m) and all other lowland populations (≤ 800 m). We revealed non-synonymous mutations in 13 of the candidate genes associated to either altitude, precipitation or cold tolerance and identified an isolation-by-environment differentiation pattern.
Conclusion: Other than the expected gradual differentiation along the altitudinal gradient, our results reveal a distinct genomic differentiation of the highland population. This finding either indicates a differential invasion history to Nepal or local high-altitude adaptation explaining the population’s phenotypic cold tolerance. In any case, this highland population can be assumed to carry pre-adapted alleles relevant for the species’ invasion into colder ecoregions worldwide that way expanding their climate niche.
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.
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 √sNN = 5.02 TeV collected by ALICE at the LHC. The 3ΛH is reconstructed 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=[72±63 (stat.)±36 (syst.)] keV are compatible with predictions from effective field theories and conclusively confirm that the 3ΛH is a weakly-bound system.
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 √sNN = 5.02 TeV collected by ALICE at the LHC. The 3ΛH is reconstructed 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=[72±63 (stat.)±35 (syst.)] keV are compatible with predictions from effective field theories and conclusively confirm that the 3ΛH is a weakly-bound system.
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 a multitude of objectives, ranging from biodiversity protection to ecosystem service provision and climate change mitigation. As available land and conservation funding are limited, optimizing resources by selecting the most beneficial PAs is vital. Here we present a decision support tool that enables a flexible approach to PA selection on a global scale, allowing different conservation objectives to be weighted and prioritized according to user-specified preferences. We apply the tool across 1347 terrestrial PAs and highlight frequent trade-offs among different objectives, e.g., between biodiversity protection and ecosystem integrity. These results indicate that decision makers must usually decide among conflicting objectives. To assist this our decision support tool provides an explicitly value-based approach that can help resolve such conflicts by considering divergent societal and political demands and values.
Spontaneous brain activity builds the foundation for human cognitive processing during external demands. Neuroimaging studies based on functional magnetic resonance imaging (fMRI) identified specific characteristics of spontaneous (intrinsic) brain dynamics to be associated with individual differences in general cognitive ability, i.e., intelligence. However, fMRI research is inherently limited by low temporal resolution, thus, preventing conclusions about neural fluctuations within the range of milliseconds. Here, we used resting-state electroencephalographical (EEG) recordings from 144 healthy adults to test whether individual differences in intelligence (Raven’s Advanced Progressive Matrices scores) can be predicted from the complexity of temporally highly resolved intrinsic brain signals. We compared different operationalizations of brain signal complexity (multiscale entropy, Shannon entropy, Fuzzy entropy, and specific characteristics of microstates) regarding their relation to intelligence. The results indicate that associations between brain signal complexity measures and intelligence are of small effect sizes (r ~ .20) and vary across different spatial and temporal scales. Specifically, higher intelligence scores were associated with lower complexity in local aspects of neural processing, and less activity in task-negative brain regions belonging to the defaultmode network. Finally, we combined multiple measures of brain signal complexity to show that individual intelligence scores can be significantly predicted with a multimodal model within the sample (10-fold cross-validation) as well as in an independent sample (external replication, N = 57). In sum, our results highlight the temporal and spatial dependency of associations between intelligence and intrinsic brain dynamics, proposing multimodal approaches as promising means for future neuroscientific research on complex human traits.
Significance Statement Spontaneous brain activity builds the foundation for intelligent processing - the ability of humans to adapt to various cognitive demands. Using resting-state EEG, we extracted multiple aspects of temporally highly resolved intrinsic brain dynamics to investigate their relationship with individual differences in intelligence. Single associations were of small effect sizes and varied critically across spatial and temporal scales. However, combining multiple measures in a multimodal cross-validated prediction model, allows to significantly predict individual intelligence scores in unseen participants. Our study adds to a growing body of research suggesting that observable associations between complex human traits and neural parameters might be rather small and proposes multimodal prediction approaches as promising tool to derive robust brain-behavior relations despite limited sample sizes.
Although vaccines are currently used to control the coronavirus disease 2019 (COVID-19) pandemic, treatment options are urgently needed for those who cannot be vaccinated and for future outbreaks involving new severe acute respiratory syndrome coronavirus virus 2 (SARS-CoV-2) strains or coronaviruses not covered by current vaccines. Thus far, few existing antivirals are known to be effective against SARS-CoV-2 and clinically successful against COVID-19.
As part of an immediate response to the COVID-19 pandemic, a high-throughput, high content imaging–based SARS-CoV-2 infection assay was developed in VeroE6-eGFP cells and was used to screen a library of 5676 compounds that passed phase 1 clinical trials. Eight candidates (nelfinavir, RG-12915, itraconazole, chloroquine, hydroxychloroquine, sematilide, remdesivir, and doxorubicin) with in vitro anti–SARS-CoV-2 activity in VeroE6-eGFP and/or Caco-2 cell lines were identified. However, apart from remdesivir, toxicity and pharmacokinetic data did not support further clinical development of these compounds for COVID-19 treatment.
Vaccines are central to controlling the coronavirus disease 2019 (COVID-19) pandemic but the durability of protection is limited for currently approved COVID-19 vaccines. Further, the emergence of variants of concern (VoCs) that evade immune recognition has reduced vaccine effectiveness, compounding the problem. Here, we show that a single dose of a murine cytomegalovirus (MCMV)-based vaccine, which expresses the spike (S) protein of the virus circulating early in the pandemic (MCMVS), protects highly susceptible K18-hACE2 mice from clinical symptoms and death upon challenge with a lethal dose of D614G SARS-CoV-2. Moreover, MCMVS vaccination controlled two immune-evading VoCs, the Beta (B.1.135) and the Omicron (BA.1) variants in BALB/c mice, and S-specific immunity was maintained for at least 5 months after immunization, where neutralizing titers against all tested VoCs were higher at 5-months than at 1-month post-vaccination. Thus, cytomegalovirus (CMV)-based vector vaccines might allow for long-term protection against COVID-19.
NAD is a coenzyme central to metabolism that was also found to serve as a 5’-terminal cap of bacterial and eukaryotic RNA species. The presence and functionality of NAD-capped RNAs (NAD-RNAs) in the archaeal domain remain to be characterized in detail. Here, by combining LC-MS and NAD captureSeq methodology, we quantified the total levels of NAD-RNAs and determined the identity of NAD-RNAs in the two model archaea, Sulfolobus acidocaldarius and Haloferax volcanii. A complementary differential RNA-Seq (dRNA-Seq) analysis revealed that NAD transcription start sites (NAD-TSS) correlate with well-defined promoter regions and often overlap with primary transcription start sites (pTSS). The population of NAD-RNAs in the two archaeal organisms shows clear differences, with S. acidocaldarius possessing more capped small non-coding RNAs (sncRNAs) and leader sequences. The NAD-cap did not prevent 5’→3’ exonucleolytic activity by the RNase Saci-aCPSF2. To investigate enzymes that facilitate the removal of the NAD-cap, four Nudix proteins of S. acidocaldarius were screened. None of the recombinant proteins showed NAD decapping activity. Instead, the Nudix protein Saci_NudT5 showed activity after incubating NAD-RNAs at elevated temperatures. Hyperthermophilic environments promote the thermal degradation of NAD into the toxic product ADPR. Incorporating NAD into RNAs and the regulation of ADPR-RNA decapping by Saci_NudT5 is proposed to provide additional layers of maintaining stable NAD levels in archaeal cells.
Importance: This study reports the first characterization of 5’-terminally modified RNA molecules in Archaea and establishes that NAD-RNA modifications, previously only identified in the other two domains of life, are also prevalent in the archaeal model organisms Sulfolobus acidocaldarius and Haloferax volcanii. We screened for NUDIX hydrolases that could remove the NAD-RNA cap and showed that none of these enzymes removed NAD modifications, but we discovered an enzyme that hydrolyzes ADPR-RNA. We propose that these activities influence the stabilization of NAD and its thermal degradation to potentially toxic ADPR products at elevated growth temperatures.
In a dynamic environment, the already limited information that human working memory can maintain needs to be constantly updated to optimally guide behaviour. Indeed, previous studies showed that working memory representations are continuously being transformed during delay periods leading up to a response. This goes hand-in-hand with the removal of task-irrelevant items. However, does such removal also include veridical, original stimuli, as they were prior to transformation? Here we aimed to assess the neural representation of task-relevant transformed representations, compared to the no-longer-relevant veridical representations they originated from. We applied multivariate pattern analysis to electroencephalographic data during maintenance of orientation gratings with and without mental rotation. During maintenance, we perturbed the representational network by means of a visual impulse stimulus, and were thus able to successfully decode veridical as well as imaginary, transformed orientation gratings from impulse-driven activity. On the one hand, the impulse response reflected only task-relevant (cued), but not task-irrelevant (uncued) items, suggesting that the latter were quickly discarded from working memory. By contrast, even though the original cued orientation gratings were also no longer task-relevant after mental rotation, these items continued to be represented next to the rotated ones, in different representational formats. This seemingly inefficient use of scarce working memory capacity was associated with reduced probe response times and may thus serve to increase precision and flexibility in guiding behaviour in dynamic environments.
Several clinically used drugs are derived from microorganisms that often produce them via non-ribosomal peptide synthetases (NRPS), giant megasynthases that activate and connect individual amino acids in an assembly line fashion. Since NRPS are not restricted to the incorporation of the 20 proteinogenic amino acids, their efficient manipulation would allow the biotechnological generation of several different peptides including linear, cyclic and further modified derivatives. Here we describe a detailed phylogenetic analysis of several bacterial NRPS that led to the identification of a new recombination breakpoint within the thiolation (T) domain important in natural NRPS evolution. From this an evolutionary-inspired eXchange Unit between T domains (XUT) approach was developed, which allows the assembly of NRPS fragments over a broad range of GC contents, protein similarities, and extender unit specificities, as was shown for the specific production of a proteasome inhibitor, designed and assembled from five different NRPS fragments.
Many clinically used drugs are derived from or inspired by bacterial natural products that often are biosynthesised via non-ribosomal peptide synthetases (NRPS), giant megasynthases that activate and join individual amino acids in an assembly line fashion. Since NRPS are not limited to the incorporation of the 20 proteinogenic amino acids, their efficient manipulation would allow the biotechnological generation of complex peptides including linear, cyclic and further modified natural product analogues, e.g. to optimise natural product leads. Here we describe a detailed phylogenetic analysis of several bacterial NRPS that led to the identification of a new recombination breakpoint within the thiolation (T) domain that is important for natural NRPS evolution. From this, an evolution-inspired eXchange Unit between T domains (XUT) approach was developed which allows the assembly of NRPS fragments over a broad range of GC contents, protein similarities, and extender unit specificities, as demonstrated for the specific production of a proteasome inhibitor designed and assembled from five different NRPS fragments.
Quantitative MRI maps of human neocortex explored using cell type-specific gene expression analysis
(2022)
Quantitative MRI (qMRI) allows extraction of reproducible and robust parameter maps. However, the connection to underlying biological substrates remains murky, especially in the complex, densely packed cortex. We investigated associations in human neocortex between qMRI parameters and neocortical cell types by comparing the spatial distribution of the qMRI parameters longitudinal relaxation rate (R1), effective transverse relaxation rate (R2∗), and magnetization transfer saturation (MTsat) to gene expression from the Allen Human Brain Atlas, then combining this with lists of genes enriched in specific cell types found in the human brain. As qMRI parameters are magnetic field strength-dependent, the analysis was performed on MRI data at 3T and 7T. All qMRI parameters significantly covaried with genes enriched in GABA- and glutamatergic neurons, i.e. they were associated with cytoarchitecture. The qMRI parameters also significantly covaried with the distribution of genes enriched in astrocytes (R2∗ at 3T, R1 at 7T), endothelial cells (R1 and MTsat at 3T), microglia (R1 and MTsat at 3T, R1 at 7T), and oligodendrocytes (R1 at 7T). These results advance the potential use of qMRI parameters as biomarkers for specific cell types.
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.
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 putative binding sites on CREs cause 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 ChIP-seq and RNA-seq data exist, they do not offer good usability, have limited support for large-scale data processing, and provide only minimal functionality for visual result interpretation.
Results We developed TF-Prioritizer, an automated java pipeline to prioritize condition-specific TFs derived from multi-modal data. TF-Prioritizer creates an interactive, feature-rich, and user-friendly web report of its results. To showcase the potential of TF-Prioritizer, we identified known active TFs (e.g., Stat5, Elf5, Nfib, Esr1), their target genes (e.g., milk proteins and cell-cycle genes), and newly classified lactating mammary gland TFs (e.g., Creb1, Arnt).
Conclusion TF-Prioritizer accepts ChIP-seq and RNA-seq data, as input and suggests TFs with differential activity, thus offering an understanding of genome-wide gene regulation, potential pathogenesis, and therapeutic targets in biomedical research.
Background: Blood donation saves lives. Provided they are in good health, male volunteers can donate as often as six times per year from the age of 18 into their late sixties. The burden of blood donation is very unevenly distributed, with a small minority of altruistic individuals providing this critical resource. While the consequences of persistent iron depletion in blood donors have been studied in the context of cancer and coronary heart disease, potential effects of the erythropoietic stress from repetitive large-volume phlebotomy remain unexplored. We sought to investigate if and how repeated blood donations affect the clonal composition of the hematopoietic stem and progenitor cell (HSPC) compartment.
Methods: 105 healthy, male individuals with an extensive blood donation history (median of 120 donations per donor; median age of 66 yrs.) were screened for the presence of clonal hematopoiesis (CH) using a sequencing panel covering 141 genes commonly mutated in human myeloid neoplasms. The control cohort consisted of 103 healthy, male donors with a median of 5 donations per donor and a median age of 63. Donors positive for CH were subsequently studied longitudinally. The pathogenicity of detected variants was compared using established scoring systems. Finally, to assess the functional consequences of blood-donation induced CH, selected CH mutations were introduced by CRISPR-mediated editing into HSPCs from human cord blood (CB) or bone marrow (BM). The effect of these mutations was tested under different stress stimuli using functional ex vivo long-term culture initiating cells (LTC-IC) assays.
Results: Compared to the control cohort, frequent donors were significantly more likely to have mutations in genes encoding for epigenetic modifiers (44.7 vs. 22.3 %), most specifically in the two genes most commonly mutated in CH, DNMT3A and TET2 (35.2 vs. 20.3 %). However, no difference in the variant allele frequency (VAF) of detected mutations was found between the groups. Longitudinal analysis revealed that the majority of the mutations remained at a stable VAF over an observation period of approximately one year. Three DNMT3A variants from the frequent donor cohort were introduced into healthy HSPCs and functionally analyzed: All expanded in response to EPO, but none responded to LPS or IFNγ stimulation. This contrasted with the leukemogenic DNMT3A R882H mutation, which did not expand in the presence of EPO but instead responded strongly to inflammatory stimuli.
Conclusions: Frequent whole blood donation is associated with a higher prevalence of CH driven by mutations in genes encoding for epigenetic modifiers, with DNMT3A and TET2 being the most common. This increased CH prevalence is not associated with a higher pathogenicity of the associated variants and is likely a result of the selection of clones with improved responsiveness to EPO under the condition of bleeding stress. Our data show that even highly frequent blood donations over many years is not increasing the risk for malignant clones further underscoring the safety of repetitive blood donations. To our knowledge, this is the first CH study analyzing a cohort of individuals known for their superior health and survival, able to donate blood until advanced age. Thus, our analysis possibly identified mutations associated with beneficial outcomes, rather than a disease condition, such as mutations in DNMT3A that mediated the improved expansion of HSPCs in EPO enriched environments. Our data support the notion of ongoing Darwinian evolution in humans at the somatic stem cell level and present EPO as one of the environmental factors to which HSPCs with specific mutations may respond with superior fitness.
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.
Multiple resistance and pH adaptation (Mrp) cation/proton antiporters are essential for growth of a variety of halophilic and alkaliphilic bacteria under stress conditions. Mrp-type antiporters are closely related to the membrane domain of respiratory complex I. We determined the structure of the Mrp antiporter from Bacillus pseudofirmus by electron cryo-microscopy at 2.2 Å resolution. The structure resolves more than 99% of the sidechains of the seven membrane subunits MrpA to MrpG plus 360 water molecules, including ∼70 in putative ion translocation pathways. Molecular dynamics simulations based on the high-resolution structure revealed details of the antiport mechanism. We find that switching the position of a histidine residue between three hydrated pathways in the MrpA subunit is critical for proton transfer that drives gated transmembrane sodium translocation. Several lines of evidence indicate that the same histidine-switch mechanism operates in respiratory complex I.
Some pitfalls of measuring representational similarity using Representational Similarity Analysis
(2022)
A core challenge in cognitive and brain sciences is to assess whether different biological systems represent the world in a similar manner. Representational Similarity Analysis (RSA) is an innovative approach that addresses this problem by looking for a second-order isomorphisim in neural activation patterns. This innovation makes it easy to compare latent representations across individuals, species and computational models, and accounts for its popularity across disciplines ranging from artificial intelligence to computational neuroscience. Despite these successes, using RSA has led to difficult-to-reconcile and contradictory findings, particularly when comparing primate visual representations with deep neural networks (DNNs): even though DNNs have been shown to learn and behave in vastly different ways to humans, comparisons based on RSA have shown striking similarities in some studies. Here, we demonstrate some pitfalls of using RSA and explain how contradictory findings can arise due to false inferences about representational similarity based on RSA-scores. In a series of studies that capture increasingly plausible training and testing scenarios, we compare neural representations in computational models, primate cortex and human cortex. These studies reveal two problematic phenomena that are ubiquitous in current research: a “mimic effect”, where confounds in stimuli can lead to high RSA-scores between provably dissimilar systems, and a “modulation effect”, where RSA-scores become dependent on stimuli used for testing. Since our results bear on a number of influential findings, such as comparisons made between human visual representations and those of primates and DNNs, we provide recommendations to avoid these pitfalls and sketch a way forward to a more solid science of representation in cognitive systems.
The pitfalls of measuring representational similarity using representational similarity analysis
(2022)
A core challenge in cognitive and brain sciences is to assess whether different biological systems represent the world in a similar manner. Representational Similarity Analysis (RSA) is an innovative approach to address this problem and has become increasingly popular across disciplines ranging from artificial intelligence to computational neuroscience. Despite these successes, RSA regularly uncovers difficult-to-reconcile and contradictory findings. Here, we demonstrate the pitfalls of using RSA and explain how contradictory findings arise due to false inferences about representational similarity based on RSA-scores. In a series of studies that capture increasingly plausible training and testing scenarios, we compare neural representations in computational models, primate cortex and human cortex. These studies reveal two problematic phenomena that are ubiquitous in current research: a “mimic” effect, where confounds in stimuli can lead to high RSA-scores between provably dissimilar systems, and a “modulation effect”, where RSA-scores become dependent on stimuli used for testing. Since our results bear on a number of influential findings and the inferences drawn by current practitioners in a wide range of disciplines, we provide recommendations to avoid these pitfalls and sketch a way forward to a more solid science of representation in cognitive systems.
The pitfalls of measuring representational similarity using representational similarity analysis
(2022)
A core challenge in neuroscience is to assess whether diverse systems represent the world similarly. Representational Similarity Analysis (RSA) is an innovative approach to address this problem and has become increasingly popular across disciplines from machine learning to computational neuroscience. Despite these successes, RSA regularly uncovers difficult-to-reconcile and contradictory findings. Here we demonstrate the pitfalls of using RSA to infer representational similarity and explain how contradictory findings arise and support false inferences when left unchecked. By comparing neural representations in primate, human and computational models, we reveal two problematic phenomena that are ubiquitous in current research: a “mimic” effect, where confounds in stimuli can lead to high RSA scores between provably dissimilar systems, and a “modulation effect”, where RSA-scores become dependent on stimuli used for testing. Since our results bear on existing findings and inferences, we provide recommendations to avoid these pitfalls and sketch a way forward.
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.
Fungi play pivotal roles in ecosystem functioning, but little is known about their global patterns of diversity, endemicity, vulnerability to global change drivers and conservation priority areas. We applied the high-resolution PacBio sequencing technique to identify fungi based on a long DNA marker that revealed a high proportion of hitherto unknown fungal taxa. We used a Global Soil Mycobiome consortium dataset to test relative performance of various sequencing depth standardization methods (calculation of residuals, exclusion of singletons, traditional and SRS rarefaction, use of Shannon index of diversity) to find optimal protocols for statistical analyses. Altogether, we used six global surveys to infer these patterns for soil-inhabiting fungi and their functional groups. We found that residuals of log-transformed richness (including singletons) against log-transformed sequencing depth yields significantly better model estimates compared with most other standardization methods. With respect to global patterns, fungal functional groups differed in the patterns of diversity, endemicity and vulnerability to main global change predictors. Unlike α-diversity, endemicity and global-change vulnerability of fungi and most functional groups were greatest in the tropics. Fungi are vulnerable mostly to drought, heat, and land cover change. Fungal conservation areas of highest priority include wetlands and moist tropical ecosystems.
The family of scaffold attachment factor B (SAFB) proteins comprises three members and was first identified as binders of the nuclear matrix/scaffold. Over the past two decades, SAFBs were shown to act in DNA repair, mRNA/(l)ncRNA processing, and as part of protein complexes with chromatin-modifying enzymes. SAFB proteins are approximately-100-kDa-sized dual nucleic acid-binding proteins with dedicated domains in an otherwise largely unstructured context, but whether and how they discriminate DNA- and RNA-binding has remained enigmatic. We here provide the SAFB2 DNA- and RNA-binding SAP and RRM domains in their functional boundaries and use solution NMR spectroscopy to ascribe DNA- and RNA-binding functions. We give insight into their target nucleic acid preferences and map the interfaces with respective nucleic acids on sparse data-derived SAP and RRM domain structures. Further, we provide evidence that the SAP domain exhibits intra-domain dynamics and a potential tendency to dimerise, which may expand its specifically targeted DNA sequence range. Our data provide a first molecular basis of and a starting point towards deciphering DNA- and RNA-binding functions of SAFB2 on the molecular level and serve a basis for understanding its localization to specific regions of chromatin and its involvement in the processing of specific RNA species.
The heterotetrameric human transfer RNA (tRNA) splicing endonuclease (TSEN) catalyzes the excision of intronic sequences from precursor tRNAs (pre-tRNAs)1. Mutations in TSEN and its associated RNA kinase CLP1 are linked to the neurodegenerative disease pontocerebellar hypoplasia (PCH)2–8. The three-dimensional (3D) assembly of TSEN/CLP1, the mechanism of substrate recognition, and the molecular details of PCH-associated mutations are not fully understood. Here, we present cryo-electron microscopy structures of human TSEN with intron-containing pre-tRNATyrgta and pre-tRNAArgtct. TSEN exhibits broad structural homology to archaeal endonucleases9 but has evolved additional regulatory elements that are involved in handling and positioning substrate RNA. Essential catalytic residues of subunit TSEN34 are organized for the 3’ splice site which emerges from a bulge-helix configuration. The triple-nucleotide bulge at the intron/3’-exon boundary is stabilized by an arginine tweezer motif of TSEN2 and an interaction with the proximal minor groove of the helix. TSEN34 and TSEN54 define the 3’ splice site by holding the tRNA body in place. TSEN54 adapts a bipartite fold with a flexible central region required for CLP1 binding. PCH-associated mutations are located far from pre-tRNA binding interfaces explaining their negative impact on structural integrity of TSEN without abrogating its catalytic activity in vitro10. Our work defines the molecular framework of pre-tRNA recognition and cleavage by TSEN and provides a structural basis to better understand PCH in the future.
Wastewater-based SARS-CoV-2 epidemiology (WBE) has been established as an important tool to support individual testing strategies. Omicron sub-variants BA.4/5 have spread globally displacing the predeceasing variants. Due to the severe transmissibility and immune escape potential of BA.4/5, early monitoring was required to asses and implement countermeasures in time.
In this study, we monitored the prevalence of SARS-CoV-2 BA.4/5 at six municipal wastewater treatment plants (WWTPs) in the Federal State of North-Rhine-Westphalia (NRW, Germany) in May and June 2022. Initially, L452R-specific primers/probes originally designed for SARS-CoV-2 Delta detection were validated using inactivated authentic viruses and evaluated for their suitability to detect BA.4/5. Subsequently, the assay was used for RT-qPCR analysis of RNA purified from wastewater obtained twice a week at six WWTPs. The occurrence of L452R carrying RNA was detected in early May 2022 and the presence of BA.4/5 was confirmed by variant-specific single nucleotide polymorphism PCR (SNP-PCR) targeting E484A/F486V. Finally, the mutant fractions were quantitatively monitored by digital PCR confirming BA.4/5 as the majority variant by 5th June 2022.
In conclusions, the successive workflow using RT-qPCR, variant-specific SNP-PCR, and RT-dPCR demonstrates the strength of WBE as a versatile tool to rapidly monitor variant spreading independent of individual test capacities.
Wastewater-based SARS-CoV-2 epidemiology (WBE) has been established as an important tool to support individual testing strategies. Omicron sub-variants BA.4/5 have spread globally displacing the predeceasing variants. Due to the severe transmissibility and immune escape potential of BA.4/5, early monitoring was required to asses and implement countermeasures in time.
In this study, we monitored the prevalence of SARS-CoV-2 BA.4/5 at six municipal wastewater treatment plants (WWTPs) in the Federal State of North-Rhine-Westphalia (NRW, Germany) in May and June 2022. Initially, L452R-specific primers/probes originally designed for SARS-CoV-2 Delta detection were validated using inactivated authentic viruses and evaluated for their suitability to detect BA.4/5. Subsequently, the assay was used for RT-qPCR analysis of RNA purified from wastewater obtained twice a week at six WWTPs. The occurrence of L452R carrying RNA was detected in early May 2022 and the presence of BA.4/5 was confirmed by variant-specific single nucleotide polymorphism PCR (SNP-PCR) targeting E484A/F486V. Finally, the mutant fractions were quantitatively monitored by digital PCR confirming BA.4/5 as the majority variant by 5th June 2022.
In conclusions, the successive workflow using RT-qPCR, variant-specific SNP-PCR, and RT-dPCR demonstrates the strength of WBE as a versatile tool to rapidly monitor variant spreading independent of individual test capacities.
Background Overweight and decreased physical fitness are highly prevalent in schizophrenia, represent a major risk factor for cardio-vascular diseases and decrease the patients’ life expectancies. It is thus important to understand the underlying mechanisms that link psychopathology and weight gain. We hypothesize that the dopaminergic reward system plays an important role in this.
Methods: We analyzed the seed-based functional connectivity (FC) of the ventral tegmental area (VTA) in a group of schizophrenic patients (n = 32) and age- as well as gender matched healthy controls (n = 27). We then correlated the resting-state results with physical fitness parameters, obtained in a fitness test, and psychopathology.
Results: The seed-based connectivity analysis revealed decreased functional connections between the VTA and the anterior cingulate cortex (ACC), as well as the dorsolateral prefrontal cortex and increased functional connectivity between the VTA and the middle temporal gyrus in patients compared to healthy controls. The decreased FC between the VTA and the ACC of the patient group could further be associated with increased body fat and negatively correlated with the overall physical fitness. We found no significant correlations with psychopathology.
Conclusion: Although we did not find significant correlations with psychopathology, we could link decreased physical fitness and high body fat with dysconnectivity between the VTA and the ACC in schizophrenia. These findings demonstrate that a dysregulated reward system is not just responsible for symptomatology in schizophrenia but is also involved in comorbidities and could pave the way for future lifestyle therapy interventions.
The antiviral drugs tecovirimat, brincidofovir, and cidofovir are considered for mpox (monkeypox) treatment despite a lack of clinical evidence. Moreover, their use is affected by toxic side-effects (brincidofovir, cidofovir), limited availability (tecovirimat), and potentially by resistance formation. Hence, additional, readily available drugs are needed. Here, therapeutic concentrations of nitroxoline, a hydroxyquinoline antibiotic with a favourable safety profile in humans, inhibited the replication of 12 mpox virus isolates from the current outbreak in primary cultures of human keratinocytes and fibroblasts and a skin explant model by interference with host cell signalling. Tecovirimat, but not nitroxoline, treatment resulted in rapid resistance development. Nitroxoline remained effective against the tecovirimat-resistant strain and increased the anti-mpox virus activity of tecovirimat and brincidofovir. Moreover, nitroxoline inhibited bacterial and viral pathogens that are often co-transmitted with mpox. In conclusion, nitroxoline is a repurposing candidate for the treatment of mpox due to both antiviral and antimicrobial activity.
Our lives (and deaths) have by now been dominated for two years by COVID-19, a pandemic that has caused hundreds of millions of disease cases, millions of deaths, trillions in economic costs, and major restrictions on our freedom. Here we suggest a novel tool for controlling the COVID-19 pandemic. The key element is a method for a population-scale PCR-based testing, applied on a systematic and repeated basis. For this we have developed a low cost, highly sensitive virus-genome-based test. Using Germany as an example, we demonstrate by using a mathematical model, how useful this strategy could have been in controlling the pandemic. We show using real-world examples how this might be implemented on a mass scale and discuss the feasibility of this approach.
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 most basic behavioural states of animals can be described as active or passive. However, while high-resolution observations of activity patterns can provide insights into the ecology of animal species, few methods are able to measure the activity of individuals of small taxa in their natural environment. We present a novel approach in which the automated VHF radio-tracking of small vertebrates fitted with lightweight transmitters (< 0.2 g) is used to distinguish between active and passive behavioural states.
A dataset containing > 3 million VHF signals was used to train and test a random forest model in the assignment of either active or passive behaviour to individuals from two forest-dwelling bat species (Myotis bechsteinii (n = 50) and Nyctalus leisleri (n = 20)). The applicability of the model to other taxonomic groups was demonstrated by recording and classifying the behaviour of a tagged bird and by simulating the effect of different types of vertebrate activity with the help of humans carrying transmitters. The random forest model successfully classified the activity states of bats as well as those of birds and humans, although the latter were not included in model training (F-score 0.96–0.98).
The utility of the model in tackling ecologically relevant questions was demonstrated in a study of the differences in the daily activity patterns of the two bat species. The analysis showed a pronounced bimodal activity distribution of N. leisleri over the course of the night while the night-time activity of M. bechsteinii was relatively constant. These results show that significant differences in the timing of species activity according to ecological preferences or seasonality can be distinguished using our method.
Our approach enables the assignment of VHF signal patterns to fundamental behavioural states with high precision and is applicable to different terrestrial and flying vertebrates. To encourage the broader use of our radio-tracking method, we provide the trained random forest models together with an R-package that includes all necessary data-processing functionalities. In combination with state-of-the-art open-source automated radio-tracking, this toolset can be used by the scientific community to investigate the activity patterns of small vertebrates with high temporal resolution, even in dense vegetation.
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.
Selective attention implements preferential routing of attended stimuli, likely through increasing the influence of the respective synaptic inputs on higher-area neurons. As the inputs of competing stimuli converge onto postsynaptic neurons, presynaptic circuits might offer the best target for attentional top-down influences. If those influences enabled presynaptic circuits to selectively entrain postsynaptic neurons, this might lead to selective routing. Indeed, when two visual stimuli induce two gamma rhythms in V1, only the gamma induced by the attended stimulus entrains gamma in V4. Here, we modeled this selective entrainment with a Dynamic Causal Model for Cross-Spectral Densities and found that it can be explained by attentional modulation of intrinsic V1 connections. Specifically, local inhibition was decreased in the granular input layer and increased in the supragranular output layer of the V1 circuit that processed the attended stimulus. Thus, presynaptic attentional influences and ensuing entrainment were sufficient to mediate selective routing.
Recent findings in permanent cell lines suggested that SARS-CoV-2 Omicron BA.1 induces a stronger interferon response than Delta. Here, we show that BA.1 and BA.5 but not Delta induce an antiviral state in air-liquid interface (ALI) cultures of primary human bronchial epithelial (HBE) cells and primary human monocytes. Both Omicron subvariants caused the production of biologically active type I (α/β) and III (λ) interferons and protected cells from super-infection with influenza A viruses. Notably, abortive Omicron infection of monocytes was sufficient to protect monocytes from influenza A virus infection. Interestingly, while influenza-like illnesses surged during the Delta wave in England, their spread rapidly declined upon the emergence of Omicron. Mechanistically, Omicron-induced interferon signalling was mediated via double-stranded RNA recognition by MDA5, as MDA5 knock-out prevented it. The JAK/ STAT inhibitor baricitinib inhibited the Omicron-mediated antiviral response, suggesting it is caused by MDA5-mediated interferon production, which activates interferon receptors that then trigger JAK/ STAT signalling. In conclusion, our study 1) demonstrates that only Omicron but not Delta induces a substantial interferon response in physiologically relevant models, 2) shows that Omicron infection protects cells from influenza A virus super-infection, and 3) indicates that BA.1 and BA.5 induce comparable antiviral states.
The COVID-19 pandemic and the associated prevention measures did not only impact on the transmission of COVID-19 but also on the spread of other infectious diseases in an unprecedented natural experiment. Here, we analysed the transmission patterns of 22 different infectious diseases during the COVID-19 pandemic in England. Our results show that the COVID-19 prevention measures generally reduced the spread of pathogens that are transmitted via the air and the faecal-oral route. Moreover, the COVID-19 prevention measures resulted in the sustained suppression of vaccine-preventable infectious diseases also after the removal of restrictions, while non-vaccine preventable diseases displayed a rapid rebound. Despite concerns that a lack of exposure to common pathogens may affect population immunity and result in large outbreaks by various pathogens post-COVID-19, only four of the 22 investigated diseases and disease groups displayed higher post-than pre-pandemic levels without an obvious causative relationship. Notably, this included chickenpox for which an effective vaccine is available but not used in the UK, which provides strong evidence supporting the inclusion of the chickenpox vaccination into the routine vaccination schedule in the UK. In conclusion, our findings provide unique, novel insights into the impact of non-pharmaceutical interventions on the spread of a broad range of infectious diseases.
Omicron BA.1 variant isolates were previously shown to replicate less effectively in interferon-competent cells and to be more sensitive to interferon treatment than a Delta isolate. Here, an Omicron BA.2 isolate displayed intermediate replication patterns in interferon-competent Caco-2-F03 cells when compared to BA.1 and Delta isolates. Moreover, BA.2 was less sensitive than BA.1 and similarly sensitive as Delta to betaferon treatment. Delta and BA.1 displayed similar sensitivity to the approved anti-SARS-CoV-2 drugs remdesivir, nirmatrelvir, EIDD-1931 (the active metabolite of molnupiravir) and the protease inhibitor aprotinin, whereas BA.2 was less sensitive than Delta and BA.1 to EIDD-1931, nirmatrelvir and aprotinin. Nirmatrelvir, EIDD-1931, and aprotinin (but not remdesivir) exerted synergistic antiviral activity in combination with betaferon, with some differences in the extent of synergism detected between the different SARS-CoV-2 variants. In conclusion, even closely related SARS-CoV-2 (sub)variants can differ in their biology and in their response to antiviral treatments. Betaferon combinations with nirmatrelvir and, in particular, with EIDD-1931 and aprotinin displayed high levels of synergism, which makes them strong candidates for clinical testing. Notably, effective antiviral combination therapies are desirable, as a higher efficacy is expected to reduce resistance formation.
Different modification pathways for m1A58 incorporation in yeast elongator and initiator tRNAs
(2022)
As essential components of the cellular protein synthesis machineries, tRNAs undergo a tightly controlled biogenesis process, which include the incorporation of a large number of posttranscriptional chemical modifications. Maturation defaults resulting in lack of modifications in the tRNA core may lead to the degradation of hypomodified tRNAs by the rapid tRNA decay (RTD) and nuclear surveillance pathways. Although modifications are typically introduced in tRNAs independently of each other, several modification circuits have been identified in which one or more modifications stimulate or repress the incorporation of others. We previously identified m1A58 as a late modification introduced after more initial modifications, such as Ѱ55 and T54 in yeast elongator tRNAPhe. However, previous reports suggested that m1A58 is introduced early along the tRNA modification process, with m1A58 being introduced on initial transcripts of initiator tRNAiMet, and hence preventing its degradation by the nuclear surveillance and RTD pathways. Here, aiming to reconcile this apparent inconsistency on the temporality of m1A58 incorporation, we examined the m1A58 modification pathways in yeast elongator and initiator tRNAs. For that, we first implemented a generic approach enabling the preparation of tRNAs containing specific modifications. We then used these specifically modified tRNAs to demonstrate that the incorporation of T54 in tRNAPhe is directly stimulated by Ѱ55, and that the incorporation of m1A58 is directly and individually stimulated by Ѱ55 and T54, thereby reporting on the molecular aspects controlling the Ѱ55 → T54 → m1A58 modification circuit in yeast elongator tRNAs. We also show that m1A58 is efficiently introduced on unmodified tRNAiMet, and does not depend on prior modifications. Finally, we show that the m1A58 single modification has tremendous effects on the structural properties of yeast tRNAiMet, with the tRNA elbow structure being properly assembled only when this modification is present. This rationalizes on structural grounds the degradation of hypomodified tRNAiMet lacking m1A58 by the nuclear surveillance and RTD pathways.
mRNA localization to subcellular compartments has been reported across all kingdoms of life and it is generally believed to promote asymmetric protein synthesis and localization. In striking contrast to previous observations, we show that in S. cerevisiae the B-type cyclin CLB2 mRNA is localized and translated in the yeast bud, while the Clb2 protein, a key regulator of mitosis progression, is concentrated in the mother nucleus. Using single-molecule RNA imaging in fixed (smFISH) and living cells (MS2 system), we show that the CLB2 mRNA is transported to the yeast bud by the She2-She3 complex, via an mRNA ZIP-code situated in the coding sequence. In CLB2 mRNA localization mutants, Clb2 protein synthesis in the bud is decreased resulting in changes in cell cycle distribution and genetic instability. Altogether, we propose that CLB2 mRNA localization acts as a sensor for bud development to couple cell growth and cell cycle progression, revealing a novel function for mRNA localization.
Long non-coding RNAs (lncRNAs) can act as regulatory RNAs which, by altering the expression of target genes, impact on the cellular phenotype and cardiovascular disease development. Endothelial lncRNAs and their vascular functions are largely undefined. Deep RNA-Seq and FANTOM5 CAGE analysis revealed the lncRNA LINC00607 to be highly enriched in human endothelial cells. LINC00607 was induced in response to hypoxia, arteriosclerosis regression in non-human primates and also in response to propranolol used to induce regression of human arteriovenous malformations. siRNA knockdown or CRISPR/Cas9 knockout of LINC00607 attenuated VEGF-A-induced angiogenic sprouting. LINC00607 knockout in endothelial cells also integrated less into newly formed vascular networks in an in vivo assay in SCID mice. Overexpression of LINC00607 in CRISPR knockout cells restored normal endothelial function. RNA- and ATAC-Seq after LINC00607 knockout revealed changes in the transcription of endothelial gene sets linked to the endothelial phenotype and in chromatin accessibility around ERG-binding sites. Mechanistically, LINC00607 interacted with the SWI/SNF chromatin remodeling protein BRG1. CRISPR/Cas9-mediated knockout of BRG1 in HUVEC followed by CUT&RUN revealed that BRG1 is required to secure a stable chromatin state, mainly on ERG-binding sites. In conclusion, LINC00607 is an endothelial-enriched lncRNA that maintains ERG target gene transcription by interacting with the chromatin remodeler BRG1.
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.
The knowledge that brain functional connectomes are both unique and reliable has enabled behaviourally relevant inferences at a subject level. However, it is unknown whether such “fingerprints” persist under altered states of consciousness. Ayahuasca is a potent serotonergic psychedelic which elicits a widespread dysregulation of functional connectivity. Used communally in religious ceremonies, its shared use may highlight relevant novel interactions between mental state and FC inherency. Using 7T fMRI, we assessed resting-state static and dynamic FCs for 21 Santo Daime members after collective ayahuasca intake in an acute, within-subject study. Here, connectome fingerprinting revealed a shared functional space, accompanied by a spatiotemporal reallocation of keypoint edges. Importantly, we show that interindividual differences in higher-order FCs motifs are relevant to experiential phenotypes, given that they can predict perceptual drug effects. Collectively, our findings offer an example as to how individualised connectivity markers can be used to trace a subject’s functional connectome across altered states of consciousness.
Reliable, easy-to-handle phenotypic screening platforms are needed for the identification of anti-SARS-CoV-2 compounds. Here, we present caspase 3/7 activity as a read-out for monitoring the replication of SARS-CoV-2 isolates from different variants, including a remdesivir-resistant strain, and of other coronaviruses in a broad range of cell culture models, independently of cytopathogenic effect formation. Compared to other cell culture models, the Caco-2 subline Caco-2-F03 displayed superior performance, as it possesses a stable SARS-CoV-2 susceptible phenotype and does not produce false-positive hits due to drug-induced phospholipidosis. A proof-of-concept screen of 1796 kinase inhibitors identified known and novel antiviral drug candidates including inhibitors of PHGDH, CLK-1, and CSF1R. The activity of the PHGDH inhibitor NCT-503 was further increased in combination with the HK2 inhibitor 2-deoxy-D-glucose, which is in clinical development for COVID-19. In conclusion, caspase 3/7 activity detection in SARS-CoV-2-infected Caco-2F03 cells provides a simple phenotypic high-throughput screening platform for SARS-CoV-2 drug candidates that reduces false positive hits.
The change in allele frequencies within a population over time represents a fundamental process of evolution. By monitoring allele frequencies, we can analyze the effects of natural selection and genetic drift on populations. To efficiently track time-resolved genetic change, large experimental or wild populations can be sequenced as pools of individuals sampled over time using high-throughput genome sequencing (called the Evolve & Resequence approach, E&R). Here, we present a set of experiments using hundreds of natural genotypes of the model plant Arabidopsis thaliana to showcase the power of this approach to study rapid evolution at large scale. First, we validate that sequencing DNA directly extracted from pools of flowers from multiple plants -- organs that are relatively consistent in size and easy to sample -- produces comparable results to other, more expensive state-of-the-art approaches such as sampling and sequencing of individual leaves. Sequencing pools of flowers from 25-50 individuals at ∼40X coverage recovers genome-wide frequencies in diverse populations with accuracy r > 0.95. Secondly, to enable analyses of evolutionary adaptation using E&R approaches of plants in highly replicated environments, we provide open source tools that streamline sequencing data curation and calculate various population genetic statistics two orders of magnitude faster than current software. To directly demonstrate the usefulness of our method, we conducted a two-year outdoor evolution experiment with A. thaliana to show signals of rapid evolution in multiple genomic regions. We demonstrate how these laboratory and computational Pool-seq-based methods can be scaled to study hundreds of populations across many climates.
Motivation Expert curation to differentiate between functionally diverged homologs and those that may still share a similar function routinely relies on the visual interpretation of domain architecture changes. However, the size of contemporary data sets integrating homologs from hundreds to thousands of species calls for alternate solutions. Scoring schemes to evaluate domain architecture similarities can help to automatize this procedure, in principle. But existing schemes are often too simplistic in the similarity assessment, many require an a-priori resolution of overlapping domain annotations, and those that allow overlaps to extend the set of annotations sources cannot account for redundant annotations. As a consequence, the gap between the automated similarity scoring and the similarity assessment based on visual architecture comparison is still too wide to make the integration of both approaches meaningful.
Results Here, we present FAS, a scoring system for the comparison of multi-layered feature architectures integrating information from a broad spectrum of annotation sources. Feature architectures are represented as directed acyclic graphs, and redundancies are resolved in the course of comparison using a score maximization algorithm. A benchmark using more than 10,000 human-yeast ortholog pairs reveals that FAS consistently outperforms existing scoring schemes. Using three examples, we show how automated architecture similarity assessments can be routinely applied in the benchmarking of orthology assignment software, in the identification of functionally diverged orthologs, and in the identification of entries in protein collections that most likely stem from a faulty gene prediction.
TriMem: a parallelized hybrid Monte Carlo software for efficient simulations of lipid membranes
(2022)
Lipid membranes are integral building blocks of living cells and perform a multitude of biological functions. Currently, molecular simulations of cellular-scale membrane structures at atomic resolution are nearly impossible, due to their size, complexity, and the large times-scales required. Instead, elastic membrane models are used to simulate membrane topologies and transitions between them, and to infer their properties and functions. Unfortunately, efficiently parallelized open-source simulation code to do so has been lacking. Here, we present TriMem, a parallel hybrid Monte Carlo simulation engine for triangulated lipid membranes. The kernels are efficiently coded in C++ and wrapped with Python for ease-of-use. The parallel implementation of the energy and gradient calculations and of Monte Carlo flip moves of edges in the triangulated membrane enable us to simulate also large and highly curved sub-cellular structures. For validation, we reproduce phase diagrams of vesicles with varying surface-to-volume ratios and area difference. The software can tackle a range of membrane remodelling processes on sub-cellular and cellular scales. Additionally, extensive documentation make the software accessible to the broad biophysics and computational cell biology communities.
More than 75% of surface and secreted proteins are modified by covalent addition of complex sugars through N- and O-glycosylation. Unlike proteins, glycans do not typically adopt specific secondary structures and remain very mobile, influencing protein dynamics and interactions with other molecules. Glycan conformational freedom impairs complete structural elucidation of glycoproteins. Computer simulations may be used to model glycan structure and dynamics. However, such simulations typically require thousands of computing hours on specialized supercomputers, thus limiting routine use. Here, we describe a reductionist method that can be implemented on personal computers to graft ensembles of realistic glycan conformers onto static protein structures in a matter of minutes. Using this open-source pipeline, we reconstructed the full glycan cover of SARS-CoV-2 Spike protein (S-protein) and a human GABAA receptor. Focusing on S-protein, we show that GlycoSHIELD recapitulates key features of extended simulations of the glycosylated protein, including epitope masking, and provides new mechanistic insights on N-glycan impact on protein structural dynamics.
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.
Membrane receptors are central to cell-cell communication. Receptor clustering at the plasma membrane modulates physiological responses, and mesoscale receptor organization is critical for downstream signaling. Spatially restricted cluster formation of the neuropeptide Y2 hormone receptor (Y2R) was observed in vivo; however, the relevance of this confinement is not fully understood. Here, we controlled Y2R clustering in situ by a chelator nanotool. Due to the multivalent interaction, we observed a dynamic exchange in the microscale confined regions. Fast Y2R enrichment in clustered areas triggered a ligand-independent downstream signaling determined by an increase in cytosolic calcium, cell spreading, and migration. We revealed that the cell response to ligand-induced activation was amplified when cells were pre-clustered by the nanotool. Ligand-independent signaling by clustering differed from ligand-induced activation in the binding of arrestin-3 as downstream effector, which was recruited to the confined regions only in the presence of the ligand. This approach enables in situ clustering of membrane receptors and raises the possibility to explore different modalities of receptor activation.
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.
Neural computations emerge from recurrent neural circuits that comprise hundreds to a few thousand neurons. Continuous progress in connectomics, electrophysiology, and calcium imaging require tractable spiking network models that can consistently incorporate new information about the network structure and reproduce the recorded neural activity features. However, it is challenging to predict which spiking network connectivity configurations and neural properties can generate fundamental operational states and specific experimentally reported nonlinear cortical computations. Theoretical descriptions for the computational state of cortical spiking circuits are diverse, including the balanced state where excitatory and inhibitory inputs balance almost perfectly or the inhibition stabilized state (ISN) where the excitatory part of the circuit is unstable. It remains an open question whether these states can co-exist with experimentally reported nonlinear computations and whether they can be recovered in biologically realistic implementations of spiking networks. Here, we show how to identify spiking network connectivity patterns underlying diverse nonlinear computations such as XOR, bistability, inhibitory stabilization, supersaturation, and persistent activity. We established a mapping between the stabilized supralinear network (SSN) and spiking activity which allowed us to pinpoint the location in parameter space where these activity regimes occur. Notably, we found that biologically-sized spiking networks can have irregular asynchronous activity that does not require strong excitation-inhibition balance or large feedforward input and we showed that the dynamic firing rate trajectories in spiking networks can be precisely targeted without error-driven training algorithms.
Respiratory complex I in mitochondria and bacteria catalyzes the transfer of electrons from NADH to quinone (Q). The free energy available from the reaction is used to pump protons and to establish a membrane proton electrochemical gradient, which drives ATP synthesis. Even though several high-resolution structures of complex I have been resolved, how Q reduction is linked with proton pumping, remains unknown. Here, microsecond long molecular dynamics (MD) simulations were performed on Yarrowia lipolytica complex I structures where Q molecules have been resolved in the ~30 Å long Q tunnel. MD simulations of several different redox/protonation states of Q reveal the coupling between the Q dynamics and the restructuring of conserved loops and ion pairs. Oxidized quinone stabilizes towards the N2 FeS cluster, a binding mode not previously described in Yarrowia lipolytica complex I structures. On the other hand, reduced (and protonated) species tend to diffuse towards the Q binding sites closer to the tunnel entrance. Mechanistic and physiological relevance of these results are discussed.
Several studies have probed perceptual performance at different times after a self-paced motor action and found frequency-specific modulations of perceptual performance phase-locked to the action. Such action-related modulation has been reported for various frequencies and modulation strengths. In an attempt to establish a basic effect at the population level, we had a relatively large number of participants (n=50) perform a self-paced button press followed by a detection task at threshold, and we applied both fixed- and random-effects tests. The combined data of all trials and participants surprisingly did not show any significant action-related modulation. However, based on previous studies, we explored the possibility that such modulation depends on the participant’s internal state. Indeed, when we split trials based on performance in neighboring trials, then trials in periods of low performance showed an action-related modulation at ≈17 Hz. When we split trials based on the performance in the preceding trial, we found that trials following a “miss” showed an action-related modulation at ≈17 Hz. Finally, when we split participants based on their false-alarm rate, we found that participants with no false alarms showed an action-related modulation at ≈17 Hz. All these effects were significant in random-effects tests, supporting an inference on the population. Together, these findings indicate that action-related modulations are not always detectable. However, the results suggest that specific internal states such as lower attentional engagement and/or higher decision criterion are characterized by a modulation in the beta-frequency range.
Several recent studies investigated the rhythmic nature of cognitive processes that lead to perception and behavioral report. These studies used different methods, and there has not yet been an agreement on a general standard. Here, we present a way to test and quantitatively compare these methods. We simulated behavioral data from a typical experiment and analyzed these data with several methods. We applied the main methods found in the literature, namely sine-wave fitting, the Discrete Fourier Transform (DFT) and the Least Square Spectrum (LSS). DFT and LSS can be applied both on the averaged accuracy time course and on single trials. LSS is mathematically equivalent to DFT in the case of regular, but not irregular sampling - which is more common. LSS additionally offers the possibility to take into account a weighting factor which affects the strength of the rhythm, such as arousal. Statistical inferences were done either on the investigated sample (fixed-effect) or on the population (random-effect) of simulated participants. Multiple comparisons across frequencies were corrected using False-Discovery-Rate, Bonferroni, or the Max-Based approach. To perform a quantitative comparison, we calculated Sensitivity, Specificity and D-prime of the investigated analysis methods and statistical approaches. Within the investigated parameter range, single-trial methods had higher sensitivity and D-prime than the methods based on the averaged-accuracy-time-course. This effect was further increased for a simulated rhythm of higher frequency. If an additional (observable) factor influenced detection performance, adding this factor as weight in the LSS further improved Sensitivity and D-prime. For multiple comparison correction, the Max-Based approach provided the highest Specificity and D-prime, closely followed by the Bonferroni approach. Given a fixed total amount of trials, the random-effect approach had higher D-prime when trials were distributed over a larger number of participants, even though this gave less trials per participant. Finally, we present the idea of using a dampened sinusoidal oscillator instead of a simple sinusoidal function, to further improve the fit to behavioral rhythmicity observed after a reset event.
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.
Brookshire (2022) claims that previous analyses of periodicity in detection performance after a reset event suffer from extreme false-positive rates. Here we show that this conclusion is based on an incorrect implemention of a null-hypothesis of aperiodicity, and that a correct implementation confirms low false-positive rates. Furthermore, we clarify that the previously used method of shuffling-in-time, and thereby shuffling-in-phase, cleanly implements the null hypothesis of no temporal structure after the reset, and thereby of no phase locking to the reset. Moving from a corresponding phase-locking spectrum to an inference on the periodicity of the underlying process can be accomplished by parameterizing the spectrum. This can separate periodic from non-periodic components, and quantify the strength of periodicity.
The mammalian frontal and auditory cortices are important for vocal behaviour. Here, using local field potential recordings, we demonstrate for the first time that the timing and spatial pattern of oscillations in the fronto-auditory cortical network of vocalizing bats (Carollia perspicillata) predict the purpose of vocalization: echolocation or communication. Transfer entropy analyses revealed predominantly top-down (frontal-to-auditory cortex) information flow during spontaneous activity and pre-vocal periods. The dynamics of information flow depended on the behavioural role of the vocalization and on the timing relative to vocal onset. Remarkably, we observed the emergence of predominantly bottom-up (auditory-to-frontal cortex) information transfer patterns specific echolocation production, leading to self-directed acoustic feedback. Electrical stimulation of frontal areas selectively enhanced responses to echolocation sounds in auditory cortex. These results reveal unique changes in information flow across sensory and frontal cortices, potentially driven by the purpose of the vocalization in a highly vocal mammalian model.
The brains of black 6 mice (Mus musculus) and Seba’s short-tailed bats (Carollia perspicillata) weigh roughly the same and share the mammalian neocortical laminar architecture. Bats have highly developed sonar calls and social communication and are an excellent neuroethological animal model for auditory research. Mice are olfactory and somatosensory specialists and are used frequently in auditory neuroscience, particularly for their advantage of standardization and genetic tools. Investigating their potentially different general auditory processing principles would advance our understanding of how the ecological needs of a species shape the development and function of the mammalian nervous system. We compared two existing datasets, recorded with linear multichannel electrodes down the depth of the primary auditory cortex (A1) while awake, across both species while presenting repetitive stimulus trains with different frequencies (∼5 and ∼40 Hz). We found that while there are similarities between cortical response profiles in bats and mice, there was a better signal to noise ratio in bats under these conditions, which allowed for a clearer following response to stimuli trains. This was most evident at higher frequency trains, where bats had stronger response amplitude suppression to consecutive stimuli. Phase coherence was far stronger in bats during stimulus response, indicating less phase variability in bats across individual trials. These results show that although both species share cortical laminar organization, there are structural differences in relative depth of layers. Better signal to noise ratio in bats could represent specialization for faster temporal processing shaped by their individual ecological niches.
Mechanisms by which specific histone modifications regulate distinct gene regulatory networks remain little understood. We investigated how H3K79me2, a modification catalyzed by DOT1L and previously considered a general transcriptional activation mark, regulates gene expression in mammalian cardiogenesis. Early embryonic cardiomyocyte ablation of Dot1l revealed that H3K79me2 does not act as a general transcriptional activator, but rather regulates highly specific gene regulatory networks at two critical cardiogenic junctures: left ventricle patterning and postnatal cardiomyocyte cell cycle withdrawal. Mechanistic analyses revealed that H3K79me2 in two distinct domains, gene bodies and regulatory elements, synergized to promote expression of genes activated by DOT1L. Surprisingly, these analyses also revealed that H3K79me2 in specific regulatory elements contributed to silencing genes usually not expressed in cardiomyocytes. As DOT1L mutants had increased numbers of postnatal mononuclear cardiomyocytes and prolonged cardiomyocyte cell cycle activity, controlled inhibition of DOT1L might be a strategy to promote cardiac regeneration post-injury.
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.
Intraspecific genomic variability affects a species’ adaptive potential towards climatic conditions. Variation in gene content across populations and environments may point at genomic adaptations to specific environments. The lichen symbiosis, a stable association of fungal and photobiont partners, offers an excellent system to study environmentally driven gene content variation. Many species have remarkable environmental tolerances, and often form populations in different climate zones. Here we combine comparative and population genomics to assess the presence and absence of genes in high elevation and low elevation genomes of two lichenized fungi of the genus Umbilicaria. The two species have non-overlapping ranges, but occupy similar climatic niches in North America (U. phaea) and Europe (U. pustulata): high elevation populations are located in the cold temperate zone and low elevation populations in the Mediterranean zone. We assessed gene content variation along replicated elevation gradients in each of the two species, based on a total of 2050 individuals across 26 populations. Specifically, we assessed shared orthologs across species within the same climate zone, and tracked which genes increase or decrease in abundance within populations along elevation. In total, we found 16 orthogroups with shared orthologous genes in genomes at low elevation and 13 at high elevation. Coverage analysis revealed one ortholog that is exclusive to genomes at low elevation. Conserved domain search revealed domains common to the protein kinases (PKs) superfamily. We traced the discovered ortholog in populations along five replicated elevation gradients on both continents. The protein kinase gene linearly declined in abundance with increasing elevation, and was absent in the highest populations. We consider the parallel loss of an ortholog in two species and in two geographic settings a rare find, and a step forward in understanding the genomic underpinnings of climatic tolerances in lichenized fungi. In addition, the tracking of gene content variation provides a widely applicable framework for retrieving biogeographical determinants of gene presence/absence patterns. Our work provides insights into gene content variation of lichenized fungi in relation to climatic gradients, suggesting a new research direction with implications for understanding evolutionary trajectories of complex symbioses in relation to climatic change.
Tree bark constitutes ideal habitat for microbial communities, because it is a stable substrate, rich in micro-niches. Bacteria, fungi, and terrestrial microalgae together form microbial communities, which in turn support more bark-associated organisms, such as mosses, lichens, and invertebrates, thus contributing to forest biodiversity. We have a limited understanding of the diversity and biotic interactions of the bark-associated microbiome, as investigations have mainly focussed on agriculturally relevant systems and on single taxonomic groups. Here we implemented a multi-kingdom metabarcoding approach to analyse diversity and community structure of the green algal, bacterial, and fungal components of the bark-associated microbial communities of beech, the most common broadleaved tree of Central European forests. We identified the most abundant taxa, hub taxa, and co-occurring taxa. We found that tree size (as a proxy for age) is an important driver of community assembly, suggesting that environmental filtering leads to less diverse fungal and algal communities over time. Conversely, forest management intensity had negligible effects on microbial communities on bark. Our study suggests the presence of undescribed, yet ecologically meaningful taxa, especially in the fungi, and highlights the importance of bark surfaces as a reservoir of microbial diversity. Our results constitute a first, essential step towards an integrated framework for understanding microbial community assembly processes on bark surfaces, an understudied habitat and neglected component of terrestrial biodiversity. Finally, we propose a cost-effective sampling strategy to study bark-associated microbial communities across large spatial or environmental scales.
Genome mining as a biotechnological tool for the discovery of novel biosynthetic genes in lichens
(2022)
The ever-increasing demand for novel drugs highlights the need for bioprospecting unexplored taxa for their biosynthetic potential. Lichen-forming fungi (LFF) are a rich source of natural products but their implementation in pharmaceutical industry is limited, mostly because the genes corresponding to a majority of their natural products is unknown. Furthermore, it is not known to what extent these genes encode structurally novel molecules. Advance in next-generation sequencing technologies has expanded the range of organisms that could be exploited for their biosynthetic potential. In this study, we mine the genomes of nine lichen-forming fungal species of the genus Umbilicaria for biosynthetic genes, and categorize the BGCs as “associated product structurally known”, and “associated product putatively novel”. We found that about 25-30% of the biosynthetic genes are divergent when compared to the global database of BGCs comprising of 1,200,000 characterized biosynthetic genes from planta, bacteria and fungi. Out of 217 total BGCs, 43 were only distantly related to known BGCs, suggesting they encode structurally and functionally unknown natural products. Clusters encoding the putatively novel metabolic diversity comprise PKSs (30), NRPSs (12) and terpenes (1). Our study emphasizes the utility of genomic data in bioprospecting microorganisms for their biosynthetic potential and in advancing the industrial application of unexplored taxa. We highlight the untapped structural metabolic diversity encoded in the lichenized fungal genomes. To the best of our knowledge, this is the first investigation identifying genes coding for NPs with potentially novel therapeutic properties in LFF.
Tracking influenza a virus infection in the lung from hematological data with machine learning
(2022)
The tracking of pathogen burden and host responses with minimal-invasive methods during respiratory infections is central for monitoring disease development and guiding treatment decisions. Utilizing a standardized murine model of respiratory Influenza A virus (IAV) infection, we developed and tested different supervised machine learning models to predict viral burden and immune response markers, i.e. cytokines and leukocytes in the lung, from hematological data. We performed independently in vivo infection experiments to acquire extensive data for training and testing purposes of the models. We show here that lung viral load, neutrophil counts, cytokines like IFN-γ and IL-6, and other lung infection markers can be predicted from hematological data. Furthermore, feature analysis of the models shows that blood granulocytes and platelets play a crucial role in prediction and are highly involved in the immune response against IAV. The proposed in silico tools pave the path towards improved tracking and monitoring of influenza infections and possibly other respiratory infections based on minimal-invasively obtained hematological parameters.
Intrinsically disordered regions (IDRs) are essential for membrane receptor regulation but often remain unresolved in structural studies. TRPV4, a member of the TRP vanilloid channel family involved in thermo- and osmosensation, has a large N-terminal IDR of approximately 150 amino acids. With an integrated structural biology approach, we analyze the structural ensemble of the TRPV4 IDR and identify a network of regulatory elements that modulate channel activity in a hierarchical lipid-dependent manner through transient long-range interactions. A highly conserved autoinhibitory patch acts as a master regulator by competing with PIP2 binding to attenuate channel activity. Molecular dynamics simulations show that loss of the interaction between the PIP2-binding site and the membrane reduces the force exerted by the IDR on the structured core of TRPV4. This work demonstrates that IDR structural dynamics are coupled to TRPV4 activity and highlights the importance of IDRs for TRP channel function and regulation.