Fungi Unearthed: Transcripts Encoding Lignocellulolytic and Chitinolytic Enzymes in Forest Soil

BACKGROUND: Fungi are the main organisms responsible for the degradation of biopolymers such as lignin, cellulose, hemicellulose, and chitin in forest ecosystems. Soil surveys largely target fungal diversity, paying less attention to fungal activity. METHODOLOGY/PRINCIPAL FINDINGS: Here we have focused on the organic horizon of a hardwood forest dominated by sugar maple that spreads widely across Eastern North America. The sampling site included three plots receiving normal atmospheric nitrogen deposition and three that received an extra 3 g nitrogen m(2) y(1) in form of sodium nitrate pellets since 1994, which led to increased accumulation of organic matter in the soil. Our aim was to assess, in samples taken from all six plots, transcript-level expression of fungal genes encoding lignocellulolytic and chitinolytic enzymes. For this we collected RNA from the forest soil, reverse-transcribed it, and amplified cDNAs of interest, using both published primer pairs as well as 23 newly developed ones. We thus detected transcript-level expression of 234 genes putatively encoding 26 different groups of fungal enzymes, notably major ligninolytic and diverse aromatic-oxidizing enzymes, various cellulose- and hemicellulose-degrading glycoside hydrolases and carbohydrate esterases, enzymes involved in chitin breakdown, N-acetylglucosamine metabolism, and cell wall degradation. Among the genes identified, 125 are homologous to known ascomycete genes and 105 to basidiomycete genes. Transcripts corresponding to all 26 enzyme groups were detected in both control and nitrogen-supplemented plots. CONCLUSIONS/SIGNIFICANCE: Many of these enzyme groups are known to be important in soil turnover processes, but the contribution of some is probably underestimated. Our data highlight the importance of ascomycetes, as well as basidiomycetes, in important biogeochemical cycles. In the nitrogen-supplemented plots, we have detected no transcript-level gap likely to explain the observed increased carbon storage, which is more likely due to community changes and perhaps transcriptional and/or post-transcriptional down-regulation of relevant genes

Parallel Evolution of Auditory Genes for Echolocation in Bats and Toothed Whales

The ability of bats and toothed whales to echolocate is a remarkable case of convergent evolution. Previous genetic studies have documented parallel evolution of nucleotide sequences in Prestin and KCNQ4, both of which are associated with voltage motility during the cochlear amplification of signals. Echolocation involves complex mechanisms. The most important factors include cochlear amplification, nerve transmission, and signal re-coding. Herein, we screen three genes that play different roles in this auditory system. Cadherin 23 (Cdh23) and its ligand, protocadherin 15 (Pcdh15), are essential for bundling motility in the sensory hair. Otoferlin (Otof) responds to nerve signal transmission in the auditory inner hair cell. Signals of parallel evolution occur in all three genes in the three groups of echolocators—two groups of bats (Yangochiroptera and Rhinolophoidea) plus the dolphin. Significant signals of positive selection also occur in Cdh23 in the Rhinolophoidea and dolphin, and Pcdh15 in Yangochiroptera. In addition, adult echolocating bats have higher levels of Otof expression in the auditory cortex than do their embryos and non-echolocation bats. Cdh23 and Pcdh15 encode the upper and lower parts of tip-links, and both genes show signals of convergent evolution and positive selection in echolocators, implying that they may co-evolve to optimize cochlear amplification. Convergent evolution and expression patterns of Otof suggest the potential role of nerve and brain in echolocation. Our synthesis of gene sequence and gene expression analyses reveals that positive selection, parallel evolution, and perhaps co-evolution and gene expression affect multiple hearing genes that play different roles in audition, including voltage and bundle motility in cochlear amplification, nerve transmission, and brain function

Recurrent, Robust and Scalable Patterns Underlie Human Approach and Avoidance

BACKGROUND. Approach and avoidance behavior provide a means for assessing the rewarding or aversive value of stimuli, and can be quantified by a keypress procedure whereby subjects work to increase (approach), decrease (avoid), or do nothing about time of exposure to a rewarding/aversive stimulus. To investigate whether approach/avoidance behavior might be governed by quantitative principles that meet engineering criteria for lawfulness and that encode known features of reward/aversion function, we evaluated whether keypress responses toward pictures with potential motivational value produced any regular patterns, such as a trade-off between approach and avoidance, or recurrent lawful patterns as observed with prospect theory. METHODOLOGY/PRINCIPAL FINDINGS. Three sets of experiments employed this task with beautiful face images, a standardized set of affective photographs, and pictures of food during controlled states of hunger and satiety. An iterative modeling approach to data identified multiple law-like patterns, based on variables grounded in the individual. These patterns were consistent across stimulus types, robust to noise, describable by a simple power law, and scalable between individuals and groups. Patterns included: (i) a preference trade-off counterbalancing approach and avoidance, (ii) a value function linking preference intensity to uncertainty about preference, and (iii) a saturation function linking preference intensity to its standard deviation, thereby setting limits to both. CONCLUSIONS/SIGNIFICANCE. These law-like patterns were compatible with critical features of prospect theory, the matching law, and alliesthesia. Furthermore, they appeared consistent with both mean-variance and expected utility approaches to the assessment of risk. Ordering of responses across categories of stimuli demonstrated three properties thought to be relevant for preference-based choice, suggesting these patterns might be grouped together as a relative preference theory. Since variables in these patterns have been associated with reward circuitry structure and function, they may provide a method for quantitative phenotyping of normative and pathological function (e.g., psychiatric illness).National Institute on Drug Abuse (14118, 026002, 026104, DABK39-03-0098, DABK39-03-C-0098); The MGH Phenotype Genotype Project in Addiction and Mood Disorder from the Office of National Drug Control Policy - Counterdrug Technology Assessment Center; MGH Department of Radiology; the National Center for Research Resources (P41RR14075); National Institute of Neurological Disorders and Stroke (34189, 05236

Helicobacter pylori Perturbs Iron Trafficking in the Epithelium to Grow on the Cell Surface

Helicobacter pylori (Hp) injects the CagA effector protein into host epithelial cells and induces growth factor-like signaling, perturbs cell-cell junctions, and alters host cell polarity. This enables Hp to grow as microcolonies adhered to the host cell surface even in conditions that do not support growth of free-swimming bacteria. We hypothesized that CagA alters host cell physiology to allow Hp to obtain specific nutrients from or across the epithelial barrier. Using a polarized epithelium model system, we find that isogenic ΔcagA mutants are defective in cell surface microcolony formation, but exogenous addition of iron to the apical medium partially rescues this defect, suggesting that one of CagA's effects on host cells is to facilitate iron acquisition from the host. Hp adhered to the apical epithelial surface increase basolateral uptake of transferrin and induce its transcytosis in a CagA-dependent manner. Both CagA and VacA contribute to the perturbation of transferrin recycling, since VacA is involved in apical mislocalization of the transferrin receptor to sites of bacterial attachment. To determine if the transferrin recycling pathway is involved in Hp colonization of the cell surface, we silenced transferrin receptor expression during infection. This resulted in a reduced ability of Hp to colonize the polarized epithelium. To test whether CagA is important in promoting iron acquisition in vivo, we compared colonization of Hp in iron-replete vs. iron-deficient Mongolian gerbils. While wild type Hp and ΔcagA mutants colonized iron-replete gerbils at similar levels, ΔcagA mutants are markedly impaired in colonizing iron-deficient gerbils. Our study indicates that CagA and VacA act in concert to usurp the polarized process of host cell iron uptake, allowing Hp to use the cell surface as a replicative niche

Combination of searches for heavy spin-1 resonances using 139 fb−1 of proton-proton collision data at s = 13 TeV with the ATLAS detector

A combination of searches for new heavy spin-1 resonances decaying into different pairings of W, Z, or Higgs bosons, as well as directly into leptons or quarks, is presented. The data sample used corresponds to 139 fb−1 of proton-proton collisions at = 13 TeV collected during 2015–2018 with the ATLAS detector at the CERN Large Hadron Collider. Analyses selecting quark pairs (qq, bb, , and tb) or third-generation leptons (τν and ττ) are included in this kind of combination for the first time. A simplified model predicting a spin-1 heavy vector-boson triplet is used. Cross-section limits are set at the 95% confidence level and are compared with predictions for the benchmark model. These limits are also expressed in terms of constraints on couplings of the heavy vector-boson triplet to quarks, leptons, and the Higgs boson. The complementarity of the various analyses increases the sensitivity to new physics, and the resulting constraints are stronger than those from any individual analysis considered. The data exclude a heavy vector-boson triplet with mass below 5.8 TeV in a weakly coupled scenario, below 4.4 TeV in a strongly coupled scenario, and up to 1.5 TeV in the case of production via vector-boson fusion

Search for resonant production of dark quarks in the dijet final state with the ATLAS detector

This paper presents a search for a new Z′ resonance decaying into a pair of dark quarks which hadronise into dark hadrons before promptly decaying back as Standard Model particles. This analysis is based on proton-proton collision data recorded at $$\sqrt{s}$$ s = 13 TeV with the ATLAS detector at the Large Hadron Collider between 2015 and 2018, corresponding to an integrated luminosity of 139 fb−1. After selecting events containing large-radius jets with high track multiplicity, the invariant mass distribution of the two highest-transverse-momentum jets is scanned to look for an excess above a data-driven estimate of the Standard Model multijet background. No significant excess of events is observed and the results are thus used to set 95% confidence-level upper limits on the production cross-section times branching ratio of the Z′ to dark quarks as a function of the Z′ mass for various dark-quark scenarios

Electron and photon energy calibration with the ATLAS detector using LHC Run 2 data

This paper presents the electron and photon energy calibration obtained with the ATLAS detector using 140 fb-1 of LHC proton-proton collision data recorded at √(s) = 13 TeV between 2015 and 2018. Methods for the measurement of electron and photon energies are outlined, along with the current knowledge of the passive material in front of the ATLAS electromagnetic calorimeter. The energy calibration steps are discussed in detail, with emphasis on the improvements introduced in this paper. The absolute energy scale is set using a large sample of Z-boson decays into electron-positron pairs, and its residual dependence on the electron energy is used for the first time to further constrain systematic uncertainties. The achieved calibration uncertainties are typically 0.05% for electrons from resonant Z-boson decays, 0.4% at ET ∼ 10 GeV, and 0.3% at ET ∼ 1 TeV; for photons at ET ∼ 60 GeV, they are 0.2% on average. This is more than twice as precise as the previous calibration. The new energy calibration is validated using J/ψ → ee and radiative Z-boson decays

Studies of new Higgs boson interactions through nonresonant HH production in the b¯bγγ fnal state in pp collisions at √s = 13 TeV with the ATLAS detector

A search for nonresonant Higgs boson pair production in the b ¯bγγ fnal state is performed using 140 fb−1 of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded by the ATLAS detector at the CERN Large Hadron Collider. This analysis supersedes and expands upon the previous nonresonant ATLAS results in this fnal state based on the same data sample. The analysis strategy is optimised to probe anomalous values not only of the Higgs (H) boson self-coupling modifer κλ but also of the quartic HHV V (V = W, Z) coupling modifer κ2V . No signifcant excess above the expected background from Standard Model processes is observed. An observed upper limit µHH < 4.0 is set at 95% confdence level on the Higgs boson pair production cross-section normalised to its Standard Model prediction. The 95% confdence intervals for the coupling modifers are −1.4 < κλ < 6.9 and −0.5 < κ2V < 2.7, assuming all other Higgs boson couplings except the one under study are fxed to the Standard Model predictions. The results are interpreted in the Standard Model efective feld theory and Higgs efective feld theory frameworks in terms of constraints on the couplings of anomalous Higgs boson (self-)interactions

Simultaneous energy and mass calibration of large-radius jets with the ATLAS detector using a deep neural network

The energy and mass measurements of jets are crucial tasks for the Large Hadron Collider experiments. This paper presents a new calibration method to simultaneously calibrate these quantities for large-radius jets measured with the ATLAS detector using a deep neural network (DNN). To address the specificities of the calibration problem, special loss functions and training procedures are employed, and a complex network architecture, which includes feature annotation and residual connection layers, is used. The DNN-based calibration is compared to the standard numerical approach in an extensive series of tests. The DNN approach is found to perform significantly better in almost all of the tests and over most of the relevant kinematic phase space. In particular, it consistently improves the energy and mass resolutions, with a 30% better energy resolution obtained for transverse momenta pT > 500 GeV