Dual-role transcription factors stabilize intermediate expression levels.

Precise control of gene expression levels is essential for normal cell functions, yet how they are defined and tightly maintained, particularly at intermediate levels, remains elusive. Here, using a series of newly developed sequencing, imaging, and functional assays, we uncover a class of transcription factors with dual roles as activators and repressors, referred to as condensate-forming level-regulating dual-action transcription factors (TFs). They reduce high expression but increase low expression to achieve stable intermediate levels. Dual-action TFs directly exert activating and repressing functions via condensate-forming domains that compartmentalize core transcriptional unit selectively. Clinically relevant mutations in these domains, which are linked to a range of developmental disorders, impair condensate selectivity and dual-action TF activity. These results collectively address a fundamental question in expression regulation and demonstrate the potential of level-regulating dual-action TFs as powerful effectors for engineering controlled expression levels.

A midbrain-thalamus-cortex circuit reorganizes cortical dynamics to initiate movement.

Motor behaviors are often planned long before execution but only released after specific sensory events. Planning and execution are each associated with distinct patterns of motor cortex activity. Key questions are how these dynamic activity patterns are generated and how they relate to behavior. Here, we investigate the multi-regional neural circuits that link an auditory "Go cue" and the transition from planning to execution of directional licking. Ascending glutamatergic neurons in the midbrain reticular and pedunculopontine nuclei show short latency and phasic changes in spike rate that are selective for the Go cue. This signal is transmitted via the thalamus to the motor cortex, where it triggers a rapid reorganization of motor cortex state from planning-related activity to a motor command, which in turn drives appropriate movement. Our studies show how midbrain can control cortical dynamics via the thalamus for rapid and precise motor behavior.

The Crystal Structure of a Biological Insulated Transmembrane Molecular Wire.

A growing number of bacteria are recognized to conduct electrons across their cell envelope, and yet molecular details of the mechanisms supporting this process remain unknown. Here, we report the atomic structure of an outer membrane spanning protein complex, MtrAB, that is representative of a protein family known to transport electrons between the interior and exterior environments of phylogenetically and metabolically diverse microorganisms. The structure is revealed as a naturally insulated biomolecular wire possessing a 10-heme cytochrome, MtrA, insulated from the membrane lipidic environment by embedding within a 26 strand ß-barrel formed by MtrB. MtrAB forms an intimate connection with an extracellular 10-heme cytochrome, MtrC, which presents its hemes across a large surface area for electrical contact with extracellular redox partners, including transition metals and electrodes.

Structural basis of transcription reduction by a promoter-proximal +1 nucleosome.

At active human genes, the +1 nucleosome is located downstream of the RNA polymerase II (RNA Pol II) pre-initiation complex (PIC). However, at inactive genes, the +1 nucleosome is found further upstream, at a promoter-proximal location. Here, we establish a model system to show that a promoter-proximal +1 nucleosome can reduce RNA synthesis in vivo and in vitro, and we analyze its structural basis. We find that the PIC assembles normally when the edge of the +1 nucleosome is located 18 base pairs (bp) downstream of the transcription start site (TSS). However, when the nucleosome edge is located further upstream, only 10 bp downstream of the TSS, the PIC adopts an inhibited state. The transcription factor IIH (TFIIH) shows a closed conformation and its subunit XPB contacts DNA with only one of its two ATPase lobes, inconsistent with DNA opening. These results provide a mechanism for nucleosome-dependent regulation of transcription initiation.

Neural Algorithms and Circuits for Motor Planning.

The brain plans and executes volitional movements. The underlying patterns of neural population activity have been explored in the context of movements of the eyes, limbs, tongue, and head in nonhuman primates and rodents. How do networks of neurons produce the slow neural dynamics that prepare specific movements and the fast dynamics that ultimately initiate these movements? Recent work exploits rapid and calibrated perturbations of neural activity to test specific dynamical systems models that are capable of producing the observed neural activity. These joint experimental and computational studies show that cortical dynamics during motor planning reflect fixed points of neural activity (attractors). Subcortical control signals reshape and move attractors over multiple timescales, causing commitment to specific actions and rapid transitions to movement execution. Experiments in rodents are beginning to reveal how these algorithms are implemented at the level of brain-wide neural circuits.

Metabolic and nontranscriptional circadian clocks: eukaryotes.

Circadian clocks are cellular timekeeping mechanisms that coordinate behavior and physiology around the 24-h day in most living organisms. Misalignment of an organism's clock with its environment is associated with long-term adverse fitness consequences, as exemplified by the link between circadian disruption and various age-related diseases in humans. Current eukaryotic models of the circadian oscillator rely on transcription/translation feedback loop mechanisms, supplemented with accessory cytosolic loops that connect them to cellular physiology. However, mounting evidence is questioning the absolute necessity of transcription-based oscillators for circadian rhythmicity, supported by the recent discovery of oxidation-reduction cycles of peroxiredoxin proteins, which persist even in the absence of transcription. A more fundamental mechanism based on metabolic cycles could thus underlie circadian transcriptional and cytosolic rhythms, thereby promoting circadian oscillations to integral properties of cellular metabolism.

Highly selective photoelectrochemical CO2 reduction by crystal phase-modulated nanocrystals without parasitic absorption.

Photoelectrochemical (PEC) carbon dioxide (CO2) reduction (CO2R) holds the potential to reduce the costs of solar fuel production by integrating CO2 utilization and light harvesting within one integrated device. However, the CO2R selectivity on the photocathode is limited by the lack of catalytic active sites and competition with the hydrogen evolution reaction. On the other hand, serious parasitic light absorption occurs on the front-side-illuminated photocathode due to the poor light transmittance of CO2R cocatalyst films, resulting in extremely low photocurrent density at the CO2R equilibrium potential. This paper describes the design and fabrication of a photocathode consisting of crystal phase-modulated Ag nanocrystal cocatalysts integrated on illumination-reaction decoupled heterojunction silicon (Si) substrate for the selective and efficient conversion of CO2. Ag nanocrystals containing unconventional hexagonal close-packed phases accelerate the charge transfer process in CO2R reaction, exhibiting excellent catalytic performance. Heterojunction Si substrate decouples light absorption from the CO2R catalyst layer, preventing the parasitic light absorption. The obtained photocathode exhibits a carbon monoxide (CO) Faradaic efficiency (FE) higher than 90% in a wide potential range, with the maximum FE reaching up to 97.4% at -0.2 V vs. reversible hydrogen electrode. At the CO2/CO equilibrium potential, a CO partial photocurrent density of -2.7 mA cm-2 with a CO FE of 96.5% is achieved in 0.1 M KHCO3 electrolyte on this photocathode, surpassing the expensive benchmark Au-based PEC CO2R system.

High-level cognition is supported by information-rich but compressible brain activity patterns.

To efficiently yet reliably represent and process information, our brains need to produce information-rich signals that differentiate between moments or cognitive states, while also being robust to noise or corruption. For many, though not all, natural systems, these two properties are often inversely related: More information-rich signals are less robust, and vice versa. Here, we examined how these properties change with ongoing cognitive demands. To this end, we applied dimensionality reduction algorithms and pattern classifiers to functional neuroimaging data collected as participants listened to a story, temporally scrambled versions of the story, or underwent a resting state scanning session. We considered two primary aspects of the neural data recorded in these different experimental conditions. First, we treated the maximum achievable decoding accuracy across participants as an indicator of the "informativeness" of the recorded patterns. Second, we treated the number of features (components) required to achieve a threshold decoding accuracy as a proxy for the "compressibility" of the neural patterns (where fewer components indicate greater compression). Overall, we found that the peak decoding accuracy (achievable without restricting the numbers of features) was highest in the intact (unscrambled) story listening condition. However, the number of features required to achieve comparable classification accuracy was also lowest in the intact story listening condition. Taken together, our work suggests that our brain networks flexibly reconfigure according to ongoing task demands and that the activity patterns associated with higher-order cognition and high engagement are both more informative and more compressible than the activity patterns associated with lower-order tasks and lower engagement.

Modeling blood metabolite homeostatic levels reduces sample heterogeneity across cohorts.

Blood metabolite levels are affected by numerous factors, including preanalytical factors such as collection methods and geographical sites. These perturbations have caused deleterious consequences for many metabolomics studies and represent a major challenge in the metabolomics field. It is important to understand these factors and develop models to reduce their perturbations. However, to date, the lack of suitable mathematical models for blood metabolite levels under homeostasis has hindered progress. In this study, we develop quantitative models of blood metabolite levels in healthy adults based on multisite sample cohorts that mimic the current challenge. Five cohorts of samples obtained across four geographically distinct sites were investigated, focusing on approximately 50 metabolites that were quantified using 1H NMR spectroscopy. More than one-third of the variation in these metabolite profiles is due to cross-cohort variation. A dramatic reduction in the variation of metabolite levels (90%), especially their site-to-site variation (95%), was achieved by modeling each metabolite using demographic and clinical factors and especially other metabolites, as observed in the top principal components. The results also reveal that several metabolites contribute disproportionately to such variation, which could be explained by their association with biological pathways including biosynthesis and degradation. The study demonstrates an intriguing network effect of metabolites that can be utilized to better define homeostatic metabolite levels, which may have implications for improved health monitoring. As an example of the potential utility of the approach, we show that modeling gender-related metabolic differences retains the interesting variance while reducing unwanted (site-related) variance.

Unsupervised identification of significant lineages of SARS-CoV-2 through scalable machine learning methods.

Since its emergence in late 2019, SARS-CoV-2 has diversified into a large number of lineages and caused multiple waves of infection globally. Novel lineages have the potential to spread rapidly and internationally if they have higher intrinsic transmissibility and/or can evade host immune responses, as has been seen with the Alpha, Delta, and Omicron variants of concern. They can also cause increased mortality and morbidity if they have increased virulence, as was seen for Alpha and Delta. Phylogenetic methods provide the "gold standard" for representing the global diversity of SARS-CoV-2 and to identify newly emerging lineages. However, these methods are computationally expensive, struggle when datasets get too large, and require manual curation to designate new lineages. These challenges provide a motivation to develop complementary methods that can incorporate all of the genetic data available without down-sampling to extract meaningful information rapidly and with minimal curation. In this paper, we demonstrate the utility of using algorithmic approaches based on word-statistics to represent whole sequences, bringing speed, scalability, and interpretability to the construction of genetic topologies. While not serving as a substitute for current phylogenetic analyses, the proposed methods can be used as a complementary, and fully automatable, approach to identify and confirm new emerging variants.

Bioenergetics of iron snow fueling life on Europa.

The main sources of redox gradients supporting high-productivity life in the Europan and other icy ocean world oceans were proposed to be photolytically derived oxidants, such as reactive oxygen species (ROS) from the icy shell, and reductants (Fe(II), S(-II), CH4, H2) from bottom waters reacting with a (ultra)mafic seafloor. Important roadblocks to maintaining life, however, are that the degree of ocean mixing to combine redox species is unknown, and ROS damage biomolecules. Here, we envisage a unique solution using an acid mine drainage (AMD)-filled pit lakes analog system for the Europan ocean, which previous models predicted to be acidic. We hypothesize that surface-generated ROS oxidize dissolved Fe(II) resulting in Fe(III) (hydr)oxide precipitates, that settle to the seafloor as "iron snow." The iron snow provides a respiratory substrate for anaerobic microorganisms ("breathing iron"), and limits harmful ROS exposure since they are now neutralized at the ice-water interface. Based on this scenario, we calculated Gibbs energies and maximal biomass productivities of various anaerobic metabolisms for a range of pH, temperatures, and H2 fluxes. Productivity by iron reducers was greater for most environmental conditions considered, whereas sulfate reducers and methanogens were more favored at high pH. Participation of Fe in the metabolic redox processes is largely neglected in most models of Europan biogeochemistry. Our model overcomes important conceptual roadblocks to life in icy ocean worlds and broadens the potential metabolic diversity, thus increasing total primary productivity, the diversity and volume of habitable environmental niches and, ultimately, the probability of biosignature detection.

Electrifying HCOOH synthesis from CO2 building blocks over Cu-Bi nanorod arrays.

Precise electrochemical synthesis of commodity chemicals and fuels from CO2 building blocks provides a promising route to close the anthropogenic carbon cycle, in which renewable but intermittent electricity could be stored within the greenhouse gas molecules. Here, we report state-of-the-art CO2-to-HCOOH valorization performance over a multiscale optimized Cu-Bi cathodic architecture, delivering a formate Faradaic efficiency exceeding 95% within an aqueous electrolyzer, a C-basis HCOOH purity above 99.8% within a solid-state electrolyzer operated at 100 mA cm-2 for 200 h and an energy efficiency of 39.2%, as well as a tunable aqueous HCOOH concentration ranging from 2.7 to 92.1 wt%. Via a combined two-dimensional reaction phase diagram and finite element analysis, we highlight the role of local geometries of Cu and Bi in branching the adsorption strength for key intermediates like *COOH and *OCHO for CO2 reduction, while the crystal orbital Hamiltonian population analysis rationalizes the vital contribution from moderate binding strength of η2(O,O)-OCHO on Cu-doped Bi surface in promoting HCOOH electrosynthesis. The findings of this study not only shed light on the tuning knobs for precise CO2 valorization, but also provide a different research paradigm for advancing the activity and selectivity optimization in a broad range of electrosynthetic systems.

DsrMKJOP is the terminal reductase complex in anaerobic sulfate respiration.

Microbial dissimilatory sulfate reduction (DSR) is a key process in the Earth biogeochemical sulfur cycle. In spite of its importance to the sulfur and carbon cycles, industrial processes, and human health, it is still not clear how reduction of sulfate to sulfide is coupled to energy conservation. A central step in the pathway is the reduction of sulfite by the DsrAB dissimilatory sulfite reductase, which leads to the production of a DsrC-trisulfide. A membrane-bound complex, DsrMKJOP, is present in most organisms that have DsrAB and DsrC, and its involvement in energy conservation has been inferred from sequence analysis, but its precise function was so far not determined. Here, we present studies revealing that the DsrMKJOP complex of the sulfate reducer Archaeoglobus fulgidus works as a menadiol:DsrC-trisulfide oxidoreductase. Our results reveal a close interaction between the DsrC-trisulfide and the DsrMKJOP complex and show that electrons from the quinone pool reduce consecutively the DsrM hemes b, the DsrK noncubane [4Fe-4S]3+/2+ catalytic center, and finally the DsrC-trisulfide with concomitant release of sulfide. These results clarify the role of this widespread respiratory membrane complex and support the suggestion that DsrMKJOP contributes to energy conservation upon reduction of the DsrC-trisulfide in the last step of DSR.

Mimicking lightning-induced electrochemistry on the early Earth.

To test the hypothesis that an abiotic Earth and its inert atmosphere could form chemically reactive carbon- and nitrogen-containing compounds, we designed a plasma electrochemical setup to mimic lightning-induced electrochemistry under steady-state conditions of the early Earth. Air-gap electrochemical reactions at air-water-ground interfaces lead to remarkable yields, with up to 40 moles of carbon dioxide being reduced into carbon monoxide and formic acid, and 3 moles of gaseous nitrogen being fixed into nitrate, nitrite, and ammonium ions, per mole of transmitted electrons. Interfaces enable reactants (e.g., minerals) that may have been on land, in lakes, and in oceans to participate in radical and redox reactions, leading to higher yields compared to gas-phase-only reactions. Cloud-to-ground lightning strikes could have generated high concentrations of reactive molecules locally, establishing diverse feedstocks for early life to emerge and survive globally.

Oxygen-bridging Fe, Co dual-metal dimers boost reversible oxygen electrocatalysis for rechargeable Zn-air batteries.

Rechargeable zinc-air batteries (ZABs) are regarded as a remarkably promising alternative to current lithium-ion batteries, addressing the requirements for large-scale high-energy storage. Nevertheless, the sluggish kinetics involving oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) hamper the widespread application of ZABs, necessitating the development of high-efficiency and durable bifunctional electrocatalysts. Here, we report oxygen atom-bridged Fe, Co dual-metal dimers (FeOCo-SAD), in which the active site Fe-O-Co-N6 moiety boosts exceptional reversible activity toward ORR and OER in alkaline electrolytes. Specifically, FeOCo-SAD achieves a half-wave potential (E1/2) of 0.87 V for ORR and an overpotential of 310 mV at a current density of 10 mA cm-2 for OER, with a potential gap (ΔE) of only 0.67 V. Meanwhile, FeOCo-SAD manifests high performance with a peak power density of 241.24 mW cm-2 in realistic rechargeable ZABs. Theoretical calculations demonstrate that the introduction of an oxygen bridge in the Fe, Co dimer induced charge spatial redistribution around Fe and Co atoms. This enhances the activation of oxygen and optimizes the adsorption/desorption dynamics of reaction intermediates. Consequently, energy barriers are effectively reduced, leading to a strong promotion of intrinsic activity toward ORR and OER. This work suggests that oxygen-bridging dual-metal dimers offer promising prospects for significantly enhancing the performance of reversible oxygen electrocatalysis and for creating innovative catalysts that exhibit synergistic effects and electronic states.

Boosting exciton dissociation and charge transfer in CsPbBr3 QDs via ferrocene derivative ligation for CO2 photoreduction.

Photo-catalytic CO2 reduction with perovskite quantum dots (QDs) shows potential for solar energy storage, but it encounters challenges due to the intricate multi-electron photoreduction processes and thermodynamic and kinetic obstacles associated with them. This study aimed to improve photo-catalytic performance by addressing surface barriers and utilizing multiple-exciton generation in perovskite QDs. A facile surface engineering method was employed, involving the grafting of ferrocene carboxylic acid (FCA) onto CsPbBr3 (CPB) QDs, to overcome limitations arising from restricted multiple-exciton dissociation and inefficient charge transfer dynamics. Kelvin Probe Force Microscopy and XPS spectral confirmed successfully creating an FCA-modulated microelectric field through the Cs active site, thus facilitating electron transfer, disrupting surface barrier energy, and promoting multi-exciton dissociations. Transient absorption spectroscopy showed enhanced charge transfer and reduced energy barriers, resulting in an impressive CO2-to-CO conversion rate of 132.8 µmol g-1 h-1 with 96.5% selectivity. The CPB-FCA catalyst exhibited four-cycle reusability and 72 h of long-term stability, marking a significant nine-fold improvement compared to pristine CPB (14.4 µmol g-1 h-1). These results provide insights into the influential role of FCA in regulating intramolecular charge transfer, enhancing multi-exciton dissociation, and improving CO2 photoreduction on CPB QDs. Furthermore, these findings offer valuable knowledge for controlling quantum-confined exciton dissociation to enhance CO2 photocatalysis.

A synergetic cocatalyst for conversion of carbon dioxide, sunlight, and water into methanol.

The conversion of CO2 into liquid fuels, using only sunlight and water, offers a promising path to carbon neutrality. An outstanding challenge is to achieve high efficiency and product selectivity. Here, we introduce a wireless photocatalytic architecture for conversion of CO2 and water into methanol and oxygen. The catalytic material consists of semiconducting nanowires decorated with core-shell nanoparticles, with a copper-rhodium core and a chromium oxide shell. The Rh/CrOOH interface provides a unidirectional channel for proton reduction, enabling hydrogen spillover at the core-shell interface. The vectorial transfer of protons, electrons, and hydrogen atoms allows for switching the mechanism of CO2 reduction from a proton-coupled electron transfer pathway in aqueous solution to hydrogenation of CO2 with a solar-to-methanol efficiency of 0.22%. The reported findings demonstrate a highly efficient, stable, and scalable wireless system for synthesis of methanol from CO2 that could provide a viable path toward carbon neutrality and environmental sustainability.

Membrane localization accelerates association under conditions relevant to cellular signaling.

Translocation of cytoplasmic molecules to the plasma membrane is commonplace in cell signaling. Membrane localization has been hypothesized to increase intermolecular association rates; however, it has also been argued that association should be faster in the cytosol because membrane diffusion is slow. Here, we directly compare an identical association reaction, the binding of complementary DNA strands, in solution and on supported membranes. The measured rate constants show that for a 10-µm-radius spherical cell, association is 22- to 33-fold faster at the membrane than in the cytoplasm. The kinetic advantage depends on cell size and is essentially negligible for typical ~1 µm prokaryotic cells. The rate enhancement is attributable to a combination of higher encounter rates in two dimensions and a higher reaction probability per encounter.

Molecular architectures of iron complexes for oxygen reduction catalysis-Activity enhancement by hydroxide ions coupling.

Developing cost-effective and high-performance electrocatalysts for oxygen reduction reaction (ORR) is critical for clean energy generation. Here, we propose an approach to the synthesis of iron phthalocyanine nanotubes (FePc NTs) as a highly active and selective electrocatalyst for ORR. The performance is significantly superior to FePc in randomly aggregated and molecularly dispersed states, as well as the commercial Pt/C catalyst. When FePc NTs are anchored on graphene, the resulting architecture shifts the ORR potentials above the redox potentials of Fe2+/3+ sites. This does not obey the redox-mediated mechanism operative on conventional FePc with a Fe2+-N moiety serving as the active sites. Pourbaix analysis shows that the redox of Fe2+/3+ sites couples with HO- ions transfer, forming a HO-Fe3+-N moiety serving as the ORR active sites under the turnover condition. The chemisorption of ORR intermediates is appropriately weakened on the HO-Fe3+-N moiety compared to the Fe2+-N state and thus is intrinsically more ORR active.

Transcription-induced active forces suppress chromatin motion.

The organization of interphase chromosomes in a number of species is starting to emerge thanks to advances in a variety of experimental techniques. However, much less is known about the dynamics, especially in the functional states of chromatin. Some experiments have shown that the motility of individual loci in human interphase chromosome decreases during transcription and increases upon inhibiting transcription. This is a counterintuitive finding because it is thought that the active mechanical force (F) on the order of ten piconewtons, generated by RNA polymerase II (RNAPII) that is presumably transmitted to the gene-rich region of the chromatin, would render it more open, thus enhancing the mobility. We developed a minimal active copolymer model for interphase chromosomes to investigate how F affects the dynamical properties of chromatin. The movements of the loci in the gene-rich region are suppressed in an intermediate range of F and are enhanced at small F values, which has also been observed in experiments. In the intermediate F, the bond length between consecutive loci increases, becoming commensurate with the distance at the minimum of the attractive interaction between nonbonded loci. This results in a transient disorder-to-order transition, leading to a decreased mobility during transcription. Strikingly, the F-dependent change in the locus dynamics preserves the organization of the chromosome at [Formula: see text]. Transient ordering of the loci, which is not found in the polymers with random epigenetic profiles, in the gene-rich region might be a plausible mechanism for nucleating a dynamic network involving transcription factors, RNAPII, and chromatin.