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At least 1,477 records · Page 82

Distal substitutions drive divergent DNA specificity among paralogous transcription factors through subdivision of conformational space

Many genomes contain families of paralogs—proteins with divergent function that evolved from a common ancestral gene after a duplication event. To understand how paralogous transcription factors evolve divergent DNA specificities, we examined how the glucocorticoid receptor and its paralogs evolved to bind activating response elements [(+)GREs] and negative glucocorticoid response elements (nGREs). We show that binding to nGREs is a property of the glucocorticoid receptor (GR) DNA-binding domain (DBD) not shared by other members of the steroid receptor family. Using phylogenetic, structural, biochemical, and molecular dynamics techniques, we show that the ancestral DBD from which GR and its paralogs evolved was capable of binding both nGRE and (+)GRE sequences because of the ancestral DBD’s ability to assume multiple DNA-bound conformations. Subsequent amino acid substitutions in duplicated daughter genes selectively restricted protein conformational space, causing this dual DNA-binding specificity to be selectively enhanced in the GR lineage and lost in all others. Key substitutions that determined the receptors’ response element-binding specificity were far from the proteins’ DNA-binding interface and interacted epistatically to change the DBD’s function through DNA-induced allosteric mechanisms. These amino acid substitutions subdivided both the conformational and functional space of the ancestral DBD among the present-day receptors, allowing a paralogous family of transcription factors to control disparate transcriptional programs despite high sequence identity.

59 BASIC BIOLOGICAL SCIENCES↗

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks

Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set of Drosophila early embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identified 21 principal patterns (PP). Providing a compact yet biologically interpretable representation of Drosophila expression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. In conclusion, the performance of PP with the Drosophila data suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.

59 BASIC BIOLOGICAL SCIENCES↗

Grasses use an alternatively wired bHLH transcription factor network to establish stomatal identity

Significance Plants both control and are controlled by the global climate. Grasses in natural and agricultural systems participate in the exchange of atmospheric CO 2 for biosphere-derived oxygen and water vapor via microscopic epidermal valves (stomata), but how these stomata are made in grasses is unknown. Using genetic screens and targeted genome editing, we identify and characterize master transcriptional regulators of stomatal initiation in the wheat relative Brachypodium . Surprisingly, the unique stomatal form and pattern of grasses is regulated by orthologs of Arabidopsis stomatal basic helix–loop–helix (bHLH) transcription factors, although the function of individual genes and regulation of their protein products have diverged. This finding suggests that the stomatal core bHLH transcription factors are excellent breeding targets to enhance performance in grasses.

Raissig, Michael T.↗

Photoprotection during iron deficiency is mediated by the bHLH transcription factors PYE and ILR3

Iron deficiency has many adverse effects on photosynthesis, which is not surprising given that 90% of foliar iron is found in the chloroplast. Although many iron-sparing mechanisms have been documented, a mechanistic understanding of how chloroplasts adapt to iron deficiency was lacking. Here, we show that the bHLH transcription factors ILR3 and PYE are required for photoprotection during iron deficiency. Changes in chloroplast morphology under the control of these transcription factors prevents the production of harmful reactive oxygen species and allows for repair of photosystem II. Understanding how plants adapt the photosynthetic machinery during iron deficiency may allow us to optimize plant growth in soils where iron is not bioavailable.

59 BASIC BIOLOGICAL SCIENCES↗

SHP2 genetic variants in NSML-associated RASopathies disrupt the PZR–IRX transcription factor signaling axis

Noonan syndrome with multiple lentigines (NSML) is a rare autosomal dominant disorder caused by mutations inPTPN11(protein tyrosine phosphatase nonreceptor type 11) which encodes for the protein tyrosine phosphatase, SHP2. Approximately 85% of NSML patients develop hypertrophic cardiomyopathy (HCM). Here, we show that SHP2 is recruited to tyrosyl phosphorylated protein-zero related (PZR) in NSML mice. This recruitment is required for the Iroquois homeobox (IRX) transcription factors 3 and 5 to suppress BMP10 which negatively regulates postnatal cardiac growth. The protein expression of IRX3 and IRX5 was elevated in hypertrophied NSML hearts. IRX3 and IRX5 upregulation was rescued in NSML mice harboring a knock-in mutation of PZR that fails to become tyrosyl phosphorylated and recruit SHP2. NSML mice treated with low-dose dasatinib also exhibited normalized IRX3 and IRX5 expression levels. Consistent with this, BMP10 expression levels were reduced in NSML mice and rescued in PZR tyrosyl phosphorylation-deficient and low-dose dasatinib-treated NSML mice. A crystal structure of the tandem SH2 domains of SHP2 bound to tyrosyl phosphorylated PZR reveals that recruitment constrains the open SHP2 conformation to facilitate cellular-Src (c-Src) binding. Disruption of c-Src binding to SHP2 abolished IRX activation and failure to suppress BMP10. Hence, NSML-associated SHP2 genetic variants disrupt IRX transcription factor signaling to BMP10, implicating this axis as a target for RASopathy-associated HCM.

Science & Technology - Other Topics↗

Enhancing subtilisin thermostability through a modified normalized B-factor analysis and loop-grafting strategy

Rational design–guided improvement of protein thermostability typically requires identification of residues or regions contributing to instability and introduction of mutations into these residues or regions. One popular method, B-FIT, utilizes B-factors to identify unstable residues or regions and combines them with other strategies, such as directed evolution. Here, we performed structure-based engineering to improve the thermostability of the subtilisin E-S7 (SES7) peptidase. The B-value of each residue was redefined in a normalized B-factor calculation, which was implemented with a refined bioinformatics analysis strategy to identify the critical area (loop 158–162) related to flexibility and to screen for suitable thermostable motif sequences in the Protein Data Bank that can act as transplant loops. In total, we analyzed 445 structures and identified 29 thermostable motifs as candidates. Using these motifs as a starting point, we performed iterative homologous modeling to obtain a desirable chimera loop and introduced five different mutations into this loop to construct thermostable SES7 proteins. Differential scanning fluorimetry revealed increases of 7.3 °C in the melting temperature of an SES7 variant designated M5 compared with the WT. The X-ray crystallographic structure of this variant was resolved at 1.96 Å resolution. The crystal structure disclosed that M5 forms more hydrogen bonds than the WT protein, consistent with design and molecular dynamics simulation results. In summary, the modified B-FIT strategy reported here has yielded a subtilisin variant with improved thermostability and promising industrial applications, supporting the notion that this modified method is a powerful tool for protein engineering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identification and positional distribution analysis of transcription factor binding sites for genes from the wheat fl-cDNA sequences

Abstract The binding sites of transcription factors (TFs) in upstream DNA regions are called transcription factor binding sites (TFBSs). TFBSs are important elements for regulating gene expression. To date, there have been few studies on the profiles of TFBSs in plants. In total, 4,873 sequences with 5ʹ upstream regions from 8530 wheat fl-cDNA sequences were used to predict TFBSs. We found 4572 TFBSs for the MADS TF family, which was twice as many as for bHLH (1951), B3 (1951), HB superfamily (1914), ERF (1820), and AP2/ERF (1725) TFs, and was approximately four times higher than the remaining TFBS types. The percentage of TFBSs and TF members showed a distinct distribution in different tissues. Overall, the distribution of TFBSs in the upstream regions of wheat fl-cDNA sequences had significant difference. Meanwhile, high frequencies of some types of TFBSs were found in specific regions in the upstream sequences. Both TFs and fl-cDNA with TFBSs predicted in the same tissues exhibited specific distribution preferences for regulating gene expression. The tissue-specific analysis of TFs and fl-cDNA with TFBSs provides useful information for functional research, and can be used to identify relationships between tissue-specific TFs and fl-cDNA with TFBSs. Moreover, the positional distribution of TFBSs indicates that some types of wheat TFBS have different positional distribution preferences in the upstream regions of genes.

Chen, Zhen-Yong↗

High-throughput small-angle X-ray scattering reveals effective structure factor transitions linked to high-concentration antibody viscosity

High-concentration monoclonal antibody (mAb) formulations are often constrained by elevated viscosity, largely driven by protein–protein interactions, which complicates manufacturing and limits subcutaneous delivery. Early viscosity risk assessment is essential during discovery, yet traditional measurements require large sample volumes, and lack high-throughput capability. Here, we develop a high-throughput small-angle X-ray scattering (SAXS) protocol to detect mAb self-association at dilute concentrations, enabling early predictive insights into high-concentration viscosity. Synchrotron SAXS measurements were conducted for 21 mAbs formulated in a histidine buffer at pH 6.0. An initial subset of 10 mAbs analyzed across 1–150 mg/mL revealed that effective structure factor transitions in the low-q region, indicative of interparticle interactions, consistently emerged below 25 mg/mL. Subsequently, 11 additional mAbs were analyzed at 1–25 mg/mL using automated liquid handling and flow cells to enable high-throughput screening. High-viscosity mAbs exhibited detectable low-q upturns at concentrations ≤10 mg/mL, whereas low-viscosity mAbs showed downturns. A classification criterion based on effective structure factor transitions accurately classified all high- and low-viscosity mAbs at 150 mg/mL, offering a scalable, sample-efficient alternative to conventional methods. These results extend recent findings on the concentration-dependent sensitivity of SAXS to short-range attractions, demonstrating that they can emerge at lower concentrations than previously reported. This study presents the most comprehensive and diverse SAXS dataset for mAbs reported to date within a single formulation, providing a valuable resource for developing and validating coarse-grained models that can more accurately capture intermolecular interactions governing high-concentration solution behavior, thereby enabling rational antibody engineering and improved developability.

36 MATERIALS SCIENCE↗

Development of control quality factor for HVAC control loop performance assessment I—Methodology (ASHRAE RP-1587)

This article is the second paper from the ASHRAE research project RP-1587, focusing on the methodology of obtaining a control quality factor (CQF). This article presents a development of two CQFs for assessing the heating, ventilation, and air-conditioning (HVAC) control loop performance. Both CQFs are able to detect whether the control loop is able to maintain the setpoint and identify the loop's ability to handle disturbances. In addition, the reversal behaviors are assessed as well. The first CQF (CQF-Harris) is proposed based on the normalized Harris index using the recursive least squares method. This recursive least squares method is selected because of its computational efficiency compared with the maximum likelihood estimation method. The second CQF (CQF-EWMA) is based on the exponentially weighted moving average of the error ratio. The assessment scale of excellent, good, fair, bad, and failed, which indicates the quality of the HVAC control loops, is established as well. The sensitivity analysis for both CQFs is also conducted, and it provides insights on choosing the appropriate parameters to compute such CQFs. Such parameters include the sampling frequency, the length of the moving window, and the variance of the unmeasured disturbance. The field evaluations and tests of the proposed CQFs for simulated control loops and real control loops can be found in the companion paper with the title 'Development of Control Quality Factor for HVAC Control Loop Performance Assessment - III: Field Testing and Results (ASHRAE RP-1587).'

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Measuring ambient densities and Lorentz factors of gamma-ray bursts from GeV and optical observations

The Fermi satellite detected GeV flashes from cosmological gamma-ray bursts (GRBs). In two GRBs, an optical counterpart of the GeV flash was detected. Such flashes are predicted by the model of a blast wave running into a medium loaded with copious e{sup ±} pairs. Here we examine a sample of seven bursts with the best GeV+optical data and further test the model. We find that the observed light curves are in agreement with the theoretical predictions, which allows us to measure three parameters for each burst: the Lorentz factor of the explosion, its isotropic kinetic energy, and the external density. With the possible exception of GRB 090510 (the only short burst in the sample), the ambient medium is consistent with a wind from a Wolf–Rayet progenitor. The wind density parameter A=ρr{sup 2} varies in the sample around 10{sup 11} g cm{sup −1}. The initial Lorentz factor of the blast wave varies from 200 to 540, and correlates with the burst luminosity. Radiative efficiency of the prompt emission varies between 0.1 and 0.8. For the two bursts with a detected optical flash, GRB 120711A and GRB 130427A, we also estimate the magnetization of the external blast wave. Remarkably, despite its small number of free parameters, the model reproduces the entire optical light curve of GRB 120711A (with its sharp peak, fast decay, plateau, and break) as well as the GeV data. The spectra of GeV flashes are predicted to extend above 0.1 TeV, where they can be detected by ground-based Cherenkov telescopes.

79 ASTRONOMY AND ASTROPHYSICS↗

Parametric CI+MBPT calculations of Th I energies and g-factors for even states

In this study, we study energies and g-factors for a large number of levels of Th I. We found that the accuracy of configuration-interaction many-body perturbation theory can be substantially improved by using multiple adjustment parameters, which are introduced to regulate the second-order MBPT corrections for single-valence energies and Coulomb interaction. The results for energies and g-factors are in excellent agreement with experiment, with accuracy sufficient to positively assign theoretical states of given angular momentum and parity to experimental levels. Finally, this theory will be further developed in the future to treat other, even more complicated, actinides such as U I.

74 ATOMIC AND MOLECULAR PHYSICS↗

S -factor and scattering-parameter extractions from ${}^{3}\mathrm{He}+{}^{4}\mathrm{He}{ \rightarrow }^{7}\mathrm{Be}+\gamma $

Previous studies of the reaction ${}^{3}\mathrm{He}+{}^{4}\mathrm{He}\to {}^{7}\mathrm{Be}+\gamma $ have mainly focused on providing the best central value and error bar for the S factor at solar energies. Experimental measurements of this capture reaction at higher energies, the ${}^{3}\mathrm{He}$–${}^{4}\mathrm{He}$ scattering phase shifts, as well as properties of ${}^{7}\mathrm{Be}$ and its excited state, have been used to constrain the theoretical models employed for this purpose. Here we show that much more information than was previously appreciated can be extracted from angle-integrated capture data alone. We use the next-to-leading-order (NLO) amplitude in an effective field theory (EFT) for ${}^{3}\mathrm{He}+{}^{4}\mathrm{He}\to {}^{7}\mathrm{Be}+\gamma $ to perform the extrapolation. At this order the EFT describes the capture process using an s-wave scattering length and effective range, the asymptotic properties of ${}^{7}\mathrm{Be}$ and its excited state, and short-distance contributions to the E1 capture amplitude. We extract the multi-dimensional posterior of all these parameters via a Bayesian analysis that uses capture data below 2 MeV. We find that properties of the ${}^{7}\mathrm{Be}$ ground and excited states are well constrained. The total S factor $S(0)\,={0.577}_{-0.016}^{+0.015}$ keV b, while the branching ratio for excited- to ground-state capture at zero energy, ${Br}(0)={0.406}_{-0.011}^{+0.013}$, both at 68% degree of belief. This S(0) is broadly consistent with other recent evaluations, and agrees with the previously recommended value $S(0)=0.56\pm 0.03\,\,\mathrm{keV}$ b, but has a smaller error bar. We also find significant constraints on ${}^{3}\mathrm{He}$–${}^{4}\mathrm{He}$ scattering parameters, and we obtain constraints on the angular distribution of capture gamma rays, which is important for interpreting experiments. The path forward for this reaction seems to lie with better measurements of the scattering phase shifts and S(E)'s angular dependence away from zero energy, together with better understanding of the asymptotic normalization coefficients of the ${}^{7}$Be bound states' wave functions. Lastly, data on these could further reduce the uncertainty on S(0).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Simultaneous control of the electron temperature and safety factor profiles in DIII-D using model-based optimal control techniques

Future tokamak power plants will likely operate using a single, well-defined plasma scenario, either in steady state or for very long pulse lengths. In order to enhance the robustness of the scenario, feedback controllers for a variety of plasma properties will be necessary to counteract any disturbances and ensure safe operation. However, only a limited set of actuators will be available to control many different quantities. Because of this, it is necessary to develop controllers that are able to regulate multiple plasma properties using a limited set of actuators. To this end, a controller has been developed for the simultaneous regulation of both the electron temperature and safety factor profiles in DIII-D. This algorithm uses a linear quadratic integral control synthesis approach based on a linearized model of the dynamics of the two profiles. Two neural network surrogate models, NubeamNet and MMMnet, are included to improve the fidelity of the model. Furthermore, the controller has been tested in simulation using COTSIM, and has demonstrated the ability to simultaneously track changes in both the electron temperature and safety factor targets, including changes in both the magnitude and the shape of the profiles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Decoherence factor as a convolution: an interplay between a Gaussian and an exponential coherence loss

Abstract We identify and investigate the origin and nature of the transition between Gaussian and exponential forms of decoherence: the decoherence factor (that controls the time dependence of the off-diagonal terms of the density matrix expressed in the pointer basis representation) is the convolution of the Fourier transforms of the spectral density and of the overlap (between the eigenstates the environment with and without couplings to the system). Spectral density alone tends to lead to the (approximately) Gaussian decay of coherence while the overlap alone results in a (largely) exponential decay. We show that these two contributions combine as a convolution, their relative importance controlled by the strength of the system-environment coupling. The resulting decoherence factor in the strong and weak coupling limits leads to predominantly Gaussian or exponential decay, respectively, as is demonstrated with two paradigmatic examples of decoherence—a spin-bath model and the quantum Brownian motion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Velocity-dependent J-factors for annihilation radiation from cosmological simulations

Abstract We determine the dark matter pair-wise relative velocity distribution in a set of Milky Way-like halos in the Auriga and APOSTLE simulations. Focusing on the smooth halo component, the relative velocity distribution is well-described by a Maxwell-Boltzmann distribution over nearly all radii in the halo. We explore the implications for velocity-dependent dark matter annihilation, focusing on four models which scale as different powers of the relative velocity: Sommerfeld, s-wave, p-wave, and d-wave models. We show that the J-factors scale as the moments of the relative velocity distribution, and that the halo-to-halo scatter is largest for d-wave, and smallest for Sommerfeld models. The J-factor is strongly correlated with the dark matter density in the halo, and is very weakly correlated with the velocity dispersion. This implies that if the dark matter density in the Milky Way can be robustly determined, one can accurately predict the dark matter annihilation signal, without the need to identify the dark matter velocity distribution in the Galaxy.

Astronomy & Astrophysics↗

Velocity-dependent J-factors for Milky Way dwarf spheroidal analogues in cosmological simulations

We study the impact of the dark matter velocity distribution modelling on signals from velocity-dependent dark matter annihilation in Milky Way dwarf spheroidal galaxies. Using the high resolution APOSTLE simulations, we identify analogues corresponding to Milky Way dwarf spheroidal galaxies, and from these directly determine the dark matter pair-wise relative velocity distribution, and compare to best-fitting Maxwell-Boltzmann distribution models. For three velocity-dependent annihilation models, p-wave, d-wave, and the Sommerfeld model, we quantify the errors introduced when using the Maxwell-Boltzmann parameterization. We extract a simple power-law relation between the maximum circular velocity of the dwarf spheroidal analogue and the peak speed of the Maxwell-Boltzmann distribution. We show that this relation can be used to accurately calculate the dark matter relative velocity distribution, and find that it allows us to estimate the dark matter annihilation signal without the need to directly calculate the relative velocity distribution for each galaxy. The scatter in the J-factors calculated from the analogues dominates the uncertainty obtained when compared to the J-factor as determined from the observational data for each dwarf spheroidal, with the largest scatter from d-wave models and the smallest from Sommerfeld models.

79 ASTRONOMY AND ASTROPHYSICS↗

Hybrid model predictive control techniques for safety factor profile and stored energy regulation while incorporating NBI constraints

Abstract A novel hybrid Model Predictive Control (MPC) algorithm has been designed for simultaneous safety factor ( q ) profile and stored energy ( w ) control while incorporating the pulse-width-modulation constraints associated with the neutral beam injection (NBI) system. Regulation of the q -profile has been extensively shown to be a key factor for improved confinement as well as non-inductive sustainment of the plasma current. Simultaneous control of w is necessary to prevent the triggering of pressure-driven magnetohydrodynamic instabilities as the controller shapes the q profile. Conventional MPC schemes proposed for q -profile control have considered the NBI powers as continuous-time signals, ignoring the discrete-time nature of these actuators and leading in some cases to performance loss. The hybrid MPC scheme in this work has the capability of incorporating the discrete-time actuator dynamics as additional constraints. In nonlinear simulations, the proposed hybrid MPC scheme demonstrates improved q -profile+ w control performance for NSTX-U operating scenarios.

Physics↗

On infinite tensor networks, complementary recovery and type II factors

We initiate a study of local operator algebras at the boundary of infinite tensor networks, using the mathematical theory of inductive limits. In particular, we consider tensor networks in which each layer acts as a quantum code with complementary recovery, a property that features prominently in the bulk-to-boundary maps intrinsic to holographic quantum error-correcting codes. In this case, we decompose the limiting Hilbert space and the algebras of observables in a way that keeps track of the entanglement in the network. As a specific example, we describe this inductive limit for the holographic Harlow-Pastawski-Preskill-Yoshida code model and relate its algebraic and error-correction features. We find that the local algebras in this model are given by the hyperfinite type II$_\infty$ factor. Next, we discuss other networks that build upon this framework and comment on a connection between type II factors and stabilizer circuits. We conclude with a discussion of multiscale entanglement renormalization ansatz networks in which complementary recovery is broken. We argue that this breaking possibly permits a limiting type III von Neumann algebra, making them more suitable ansätze for approximating subregions of quantum field theories.

holographic dualities↗