Targeting KRAS Mutant Cancers with a Covalent G12C-Specific Inhibitor.

KRASG12C was recently identified to be potentially druggable by allele-specific covalent targeting of Cys-12 in vicinity to an inducible allosteric switch II pocket (S-IIP). Success of this approach requires active cycling of KRASG12C between its active-GTP and inactive-GDP conformations as accessibility of the S-IIP is restricted only to the GDP-bound state. This strategy proved feasible for inhibiting mutant KRAS in vitro; however, it is uncertain whether this approach would translate to in vivo. Here, we describe structure-based design and identification of ARS-1620, a covalent compound with high potency and selectivity for KRASG12C. ARS-1620 achieves rapid and sustained in vivo target occupancy to induce tumor regression. We use ARS-1620 to dissect oncogenic KRAS dependency and demonstrate that monolayer culture formats significantly underestimate KRAS dependency in vivo. This study provides in vivo evidence that mutant KRAS can be selectively targeted and reveals ARS-1620 as representing a new generation of KRASG12C-specific inhibitors with promising therapeutic potential.

Poly(ADP-ribose) drives condensation of FUS via a transient interaction.

Poly(ADP-ribose) (PAR) is an RNA-like polymer that regulates an increasing number of biological processes. Dysregulation of PAR is implicated in neurodegenerative diseases characterized by abnormal protein aggregation, including amyotrophic lateral sclerosis (ALS). PAR forms condensates with FUS, an RNA-binding protein linked with ALS, through an unknown mechanism. Here, we demonstrate that a strikingly low concentration of PAR (1 nM) is sufficient to trigger condensation of FUS near its physiological concentration (1 µM), which is three orders of magnitude lower than the concentration at which RNA induces condensation (1 µM). Unlike RNA, which associates with FUS stably, PAR interacts with FUS transiently, triggering FUS to oligomerize into condensates. Moreover, inhibition of a major PAR-synthesizing enzyme, PARP5a, diminishes FUS condensation in cells. Despite their structural similarity, PAR and RNA co-condense with FUS, driven by disparate modes of interaction with FUS. Thus, we uncover a mechanism by which PAR potently seeds FUS condensation.

R-DeeP: Proteome-wide and Quantitative Identification of RNA-Dependent Proteins by Density Gradient Ultracentrifugation.

The comprehensive but specific identification of RNA-binding proteins as well as the discovery of RNA-associated protein functions remain major challenges in RNA biology. Here we adapt the concept of RNA dependence, defining a protein as RNA dependent when its interactome depends on RNA. We converted this concept into a proteome-wide, unbiased, and enrichment-free screen called R-DeeP (RNA-dependent proteins), based on density gradient ultracentrifugation. Quantitative mass spectrometry identified 1,784 RNA-dependent proteins, including 537 lacking known links to RNA. Exploiting the quantitative nature of R-DeeP, proteins were classified as not, partially, or completely RNA dependent. R-DeeP identified the transcription factor CTCF as completely RNA dependent, and we uncovered that RNA is required for the CTCF-chromatin association. Additionally, R-DeeP allows reconstruction of protein complexes based on co-segregation. The whole dataset is available at http://R-DeeP.dkfz.de, providing proteome-wide, specific, and quantitative identification of proteins with RNA-dependent interactions and aiming at future functional discovery of RNA-protein complexes.

Activation induces shift in nutrient utilization that differentially impacts cell functions in human neutrophils.

Neutrophils utilize a variety of metabolic sources to support their crucial functions as the first responders in innate immunity. Here, through in vivo and ex vivo isotopic tracing, we examined the contributions of different nutrients to neutrophil metabolism under specific conditions. Human peripheral blood neutrophils, in contrast to a neutrophil-like cell line, rely on glycogen storage as a major metabolic source under resting state but rapidly switch to primarily using extracellular glucose upon activation with various stimuli. This shift is driven by a substantial increase in glucose uptake, enabled by rapidly increased GLUT1 on cell membrane, that dominates the simultaneous increase in gross glycogen cycling capacity. Shifts in nutrient utilization impact neutrophil functions in a function-specific manner: oxidative burst depends on glucose utilization, whereas NETosis and phagocytosis can be flexibly supported by either glucose or glycogen, and neutrophil migration and fungal control are enhanced by the shift from glycogen utilization to glucose utilization. This work provides a quantitative and dynamic understanding of fundamental features in neutrophil metabolism and elucidates how metabolic remodeling shapes neutrophil functions, which has broad health relevance.

The Proto-oncogene c-Kit Inhibits Tumor Growth by Behaving as a Dependence Receptor.

c-Kit is a classic proto-oncogene either mutated or upregulated in cancer cells, and this leads to its constitutive kinase activation and, thus, to uncontrolled proliferation. Although the pro-oncogenic role of c-Kit is of no doubt, some observations do not fit well with c-Kit solely as a tumor-promoting moiety. We show here that c-Kit actively triggers cell death in various cancer cell lines unless engaged by its ligand stem cell factor (SCF). This pro-death activity is enhanced when the kinase activation of c-Kit is silenced and is due to c-Kit intracellular cleavage by caspase-like protease at D816. Moreover, in vivo, overexpression of a c-Kit kinase-dead mutant inhibits tumor growth, and this intrinsic c-Kit tumor-suppressive activity is dependent on the D816 cleavage. Thus, c-Kit acts both as a proto-oncogene via its kinase activity and as a tumor suppressor via its dependence receptor activity.

The neuropeptide drosulfakinin enhances choosiness and protects males from the aging effects of social perception.

The motivation to reproduce is a potent natural drive, and the social behaviors that induce it can severely impact animal health and lifespan. Indeed, in Drosophila males, accelerated aging associated with reproduction arises not from the physical act of courtship or copulation but instead from the motivational drive to court and mate. To better understand the mechanisms underlying social effects on aging, we studied male choosiness for mates. We found that increased activity of insulin-producing cells (IPCs) of the fly brain potentiated choosiness without consistently affecting courtship activity. Surprisingly, this effect was not caused by insulins themselves, but instead by drosulfakinin (DSK), another neuropeptide produced in a subset of the IPCs, acting through one of the two DSK receptors, CCKLR-17D1. Activation of Dsk+ IPC neurons also decreased food consumption, while activation of Dsk+ neurons outside of IPCs affected neither choosiness nor feeding, suggesting an overlap between Dsk+neurons modulating choosiness and those influencing satiety. Broader activation of Dsk+ neurons (both within and outside of the IPCs) was required to rescue the detrimental effect of female pheromone exposure on male lifespan, as was the function of both DSK receptors. The same broad set of Dsk+ neurons was found to reinforce normally aversive feeding interactions, but only after exposure to female pheromones, suggesting that perception of the opposite sex gates rewarding properties of these neurons. We speculate that broad Dsk+ neuron activation is associated with states of satiety and social experience, which under stressful conditions is rewarding and beneficial for lifespan.

Habitat fragmentation decouples fire-stimulated flowering from plant reproductive fitness.

Many plant species in historically fire-dependent ecosystems exhibit fire-stimulated flowering. While greater reproductive effort after fire is expected to result in increased reproductive outcomes, seed production often depends on pollination, the spatial distribution of prospective mates, and the timing of their reproductive activity. Fire-stimulated flowering may thus have limited fitness benefits in small, isolated populations where mating opportunities are restricted and pollination rates are low. We conducted a 6-y study of 6,357 Echinacea angustifolia (Asteraceae) individuals across 35 remnant prairies in Minnesota (USA) to experimentally evaluate how fire effects on multiple components of reproduction vary with population size in a common species. Fire increased annual reproductive effort across populations, doubling the proportion of plants in flower and increasing the number of flower heads 65% per plant. In contrast, fire's influence on reproductive outcomes differed between large and small populations, reflecting the density-dependent effects of fire on spatiotemporal mating potential and pollination. In populations with fewer than 20 individuals, fire did not consistently increase pollination or annual seed production. Above this threshold, fire increased mating potential, leading to a 24% increase in seed set and a 71% increase in annual seed production. Our findings suggest that density-dependent effects of fire on pollination largely determine plant reproductive outcomes and could influence population dynamics across fire-dependent systems. Failure to account for the density-dependent effects of fire on seed production may lead us to overestimate the beneficial effects of fire on plant demography and the capacity of fire to maintain plant diversity, especially in fragmented habitats.

Integration of history information Drives Serial Dependence and Stabilizes Working Memory Representations.

Serial dependence has shown seemingly contradictory effects on visual perception and working memory. While serial dependence promotes perpetual and mnemonic stability, it biases behavioral reports toward prior information. The neural mechanisms that drive both biasing and adaptive stabilizing effects are not well understood. We proposed and tested a reactivation and integration mechanism that can account for these contradictory effects. We used multivariate pattern analyses of EEG data (26 human participants, 17 females, 9 males) to examine the reactivation of prior reported orientation during the delay period of a visual working memory task. The reactivation strength of prior reports, but not prior sensory items, was predictive of the magnitude of serial dependency biases. These reactivated representations integrated with the representation of the current memory item and improved the ability to decode the current contents of memory. Overall, our data provide convergent evidence suggesting that prior reports in a visual working memory task are reactivated on the subsequent trial and become integrated with current memory representations. This similarity-dependent reactivation mechanism drives both report biasing and stabilization effects attributed to serial dependence in working memory.

DLTKcat: deep learning-based prediction of temperature-dependent enzyme turnover rates.

The enzyme turnover rate, ${k}_{cat}$, quantifies enzyme kinetics by indicating the maximum efficiency of enzyme catalysis. Despite its importance, ${k}_{cat}$ values remain scarce in databases for most organisms, primarily because of the cost of experimental measurements. To predict ${k}_{cat}$ and account for its strong temperature dependence, DLTKcat was developed in this study and demonstrated superior performance (log10-scale root mean squared error = 0.88, R-squared = 0.66) than previously published models. Through two case studies, DLTKcat showed its ability to predict the effects of protein sequence mutations and temperature changes on ${k}_{cat}$ values. Although its quantitative accuracy is not high enough yet to model the responses of cellular metabolism to temperature changes, DLTKcat has the potential to eventually become a computational tool to describe the temperature dependence of biological systems.

Immune-epithelial cell cross-talk enhances antiviral responsiveness to SARS-CoV-2 in children.

The risk of developing severe COVID-19 rises dramatically with age. Schoolchildren are significantly less likely than older people to die from SARS-CoV-2 infection, but the molecular mechanisms underlying this age-dependence are unknown. In primary infections, innate immunity is critical due to the lack of immune memory. Children, in particular, have a significantly stronger interferon response due to a primed state of their airway epithelium. In single-cell transcriptomes of nasal turbinates, we find increased frequencies of immune cells and stronger cytokine-mediated interactions with epithelial cells, resulting in increased epithelial expression of viral sensors (RIG-I, MDA5) via IRF1. In vitro, adolescent peripheral blood mononuclear cells produce more cytokines, priming A549 cells for stronger interferon responses to SARS-CoV-2. Taken together, our findings suggest that increased numbers of immune cells in the airways of children and enhanced cytokine-based interactions with epithelial cells tune the setpoint of the epithelial antiviral system. Our findings shed light on the molecular basis of children's remarkable resistance to COVID-19 and may suggest a novel concept for immunoprophylactic treatments.

State-dependent effects of responsive neurostimulation depend on seizure localization.

Brain-responsive neurostimulation is firmly ensconced among treatment options for drug-resistant focal epilepsy, but over a quarter of patients treated with the RNS System do not experience meaningful seizure reduction. Initial titration of RNS therapy is typically similar for all patients, raising the possibility that treatment response might be enhanced by consideration of patient-specific variables. Indeed, small, single-center studies have yielded preliminary evidence that RNS System effectiveness depends on the brain state during which stimulation is applied. The generalizability of these findings remains unclear, however, and it is unknown whether state-dependent effects of responsive neurostimulation are also stratified by location of the seizure onset zone where stimulation is delivered. We aimed to determine whether state-dependent effects of the RNS System are evident in the large, diverse, multi-center cohort of RNS System clinical trial participants and to test whether these effects differ between mesiotemporal and neocortical epilepsies. Eighty-one of 256 patients who were treated with the RNS System across 31 centers during clinical trials met criteria for inclusion in this retrospective study. Risk states were defined in relation to phases of daily and multi-day cycles of interictal epileptiform activity that are thought to determine seizure likelihood. We found that the probabilities of risk state transitions depended on the stimulation parameter being changed, the starting seizure risk state, and the stimulated brain region. Changes in two commonly adjusted stimulation parameters, charge density and stimulation frequency, produced opposite effects on risk state transitions depending on seizure localization. Greater variance in acute risk state transitions was explained by state-dependent responsive neurostimulation for bipolar stimulation for neocortical epilepsies and for monopolar stimulation for mesiotemporal epilepsies. Variability in effectiveness of RNS System therapy across individuals may relate, at least partly, to the fact that current treatment paradigms do not account fully for fluctuations in brain states or locations of simulation sites. State-dependence of electrical brain stimulation may inform development of next-generation closed-loop devices that can detect changes in brain state and deliver adaptive, localization-specific patterns of stimulation to maximize therapeutic effects.

Neural mechanisms of sequential dependence in time perception: the impact of prior task and memory processing.

Our perception and decision-making are susceptible to prior context. Such sequential dependence has been extensively studied in the visual domain, but less is known about its impact on time perception. Moreover, there are ongoing debates about whether these sequential biases occur at the perceptual stage or during subsequent post-perceptual processing. Using functional magnetic resonance imaging, we investigated neural mechanisms underlying temporal sequential dependence and the role of action in time judgments across trials. Participants performed a timing task where they had to remember the duration of green coherent motion and were cued to either actively reproduce its duration or simply view it passively. We found that sequential biases in time perception were only evident when the preceding task involved active duration reproduction. Merely encoding a prior duration without reproduction failed to induce such biases. Neurally, we observed activation in networks associated with timing, such as striato-thalamo-cortical circuits, and performance monitoring networks, particularly when a "Response" trial was anticipated. Importantly, the hippocampus showed sensitivity to these sequential biases, and its activation negatively correlated with the individual's sequential bias following active reproduction trials. These findings highlight the significant role of memory networks in shaping time-related sequential biases at the post-perceptual stages.

Serial Dependence in Perception.

Much evidence has shown that perception is biased towards previously presented similar stimuli, an effect recently termed serial dependence. Serial dependence affects nearly every aspect of perception, often causing gross perceptual distortions, especially for weak and ambiguous stimuli. Despite unwanted side-effects, empirical evidence and Bayesian modeling show that serial dependence acts to improve efficiency and is generally beneficial to the system. Consistent with models of predictive coding, the Bayesian priors of serial dependence are generated at high levels of cortical analysis, incorporating much perceptual experience, but feed back to lower sensory areas. These feedback loops may drive oscillations in the alpha range, linked strongly with serial dependence. The discovery of top-down predictive perceptual processes is not new, but the new, more quantitative approach characterizing serial dependence promises to lead to a deeper understanding of predictive perceptual processes and their underlying neural mechanisms.

A fine balance of hydrophobic-electrostatic communication pathways in a pH-switching protein.

Allostery is the phenomenon of coupling between distal binding sites in a protein. Such coupling is at the crux of protein function and regulation in a myriad of scenarios, yet determining the molecular mechanisms of coupling networks in proteins remains a major challenge. Here, we report mechanisms governing pH-dependent myristoyl switching in monomeric hisactophilin, whereby the myristoyl moves between a sequestered state, i.e., buried within the core of the protein, to an accessible state, in which the myristoyl has increased accessibility for membrane binding. Measurements of the pH and temperature dependence of amide chemical shifts reveal protein local structural stability and conformational heterogeneity that accompany switching. An analysis of these measurements using a thermodynamic cycle framework shows that myristoyl-proton coupling at the single-residue level exists in a fine balance and extends throughout the protein. Strikingly, small changes in the stereochemistry or size of core and surface hydrophobic residues by point mutations readily break, restore, or tune myristoyl switch energetics. Synthesizing the experimental results with those of molecular dynamics simulations illuminates atomistic details of coupling throughout the protein, featuring a large network of hydrophobic interactions that work in concert with key electrostatic interactions. The simulations were critical for discerning which of the many ionizable residues in hisactophilin are important for switching and identifying the contributions of nonnative interactions in switching. The strategy of using temperature-dependent NMR presented here offers a powerful, widely applicable way to elucidate the molecular mechanisms of allostery in proteins at high resolution.

Seasonality, density dependence, and spatial population synchrony.

Studies of spatial population synchrony constitute a central approach for understanding the drivers of ecological dynamics. Recently, identifying the ecological impacts of climate change has emerged as a new important focus in population synchrony studies. However, while it is well known that climatic seasonality and sequential density dependence influences local population dynamics, the role of season-specific density dependence in shaping large-scale population synchrony has not received attention. Here, we present a widely applicable analytical protocol that allows us to account for both season and geographic context-specific density dependence to better elucidate the relative roles of deterministic and stochastic sources of population synchrony, including the renowned Moran effect. We exemplify our protocol by analyzing time series of seasonal (spring and fall) abundance estimates of cyclic rodent populations, revealing that season-specific density dependence is a major component of population synchrony. By accounting for deterministic sources of synchrony (in particular season-specific density dependence), we are able to identify stochastic components. These stochastic components include mild winter weather events, which are expected to increase in frequency under climate warming in boreal and Arctic ecosystems. Interestingly, these weather effects act both directly and delayed on the vole populations, thus enhancing the Moran effect. Our study demonstrates how different drivers of population synchrony, presently altered by climate warming, can be disentangled based on seasonally sampled population time-series data and adequate population models.

Long-range dependence and extreme values of precipitation, phosphorus load, and Cyanobacteria.

Extreme daily values of precipitation (1939-2021), discharge (1991-2021), phosphorus (P) load (1994-2021), and phycocyanin, a pigment of Cyanobacteria (June 1-September 15 of 2008-2021) are clustered as multi-day events for Lake Mendota, Wisconsin. Long-range dependence, or memory, is the shortest for precipitation and the longest for phycocyanin. Extremes are clustered for all variates and those of P load and phycocyanin are most strongly clustered. Extremes of P load are predictable from extremes of precipitation, and precipitation and P load are correlated with later concentrations of phycocyanin. However, time delays from 1 to 60 d were found between P load extremes and the next extreme phycocyanin event within the same year of observation. Although most of the lake's P enters in extreme events, blooms of Cyanobacteria may be sustained by recycling and food web processes.

Mechanism of voltage gating in the voltage-sensing phosphatase Ci-VSP.

Conformational changes in voltage-sensing domains (VSDs) are driven by the transmembrane electric field acting on the protein charges. Yet, the overall energetics and detailed mechanism of this process are not fully understood. Here, we determined free energy and displacement charge landscapes as well as the major conformations visited during a complete functional gating cycle in the isolated VSD of the phosphatase Ci-VSP (Ci-VSD) comprising four transmembrane helices (segments S1 to S4). Molecular dynamics simulations highlight the extent of S4 movements. In addition to the crystallographically determined activated "Up" and resting "Down" states, the simulations predict two Ci-VSD conformations: a deeper resting state ("down-minus") and an extended activated ("up-plus") state. These additional conformations were experimentally probed via systematic cysteine mutagenesis with metal-ion bridges and the engineering of proton conducting mutants at hyperpolarizing voltages. The present results show that these four states are visited sequentially in a stepwise manner during voltage activation, each step translocating one arginine or the equivalent of ∼1 e0 across the membrane electric field, yielding a transfer of ∼3 e0 charges in total for the complete process.

Role of dynamic bonds on fatigue threshold of tough hydrogels.

SignificanceDynamic bonds have been found to enhance fracture toughness of hydrogels as sacrificial bonds, but the role of dynamic bonds to fatigue threshold of hydrogels is poorly understood because the wide dynamic range of viscoelastic response imposes a challenge on fatigue experiments. Here, by using polyampholyte hydrogels, we adopted a time-salt superposition principle to access a wide range of time scales that are otherwise difficult to access in fatigue tests. Relations between fatigue threshold and strain rate in elastic and viscoelastic regimes and the corresponding mechanism correlated to permanent/dynamic bonds were revealed. We believe that this work gives important insight into the design and development of fatigue-resistant soft materials composed of dynamic bonds.

Size Dependent Specific Heat Capacity of PbSe Nanocrystals.

Specific heat capacity is one of the most fundamental thermodynamic properties of materials. In this work, we measured the specific heat capacity of PbSe nanocrystals with diameters ranging from 5 to 23 nm, and its value increases significantly from 0.2 to 0.6 J g-1 °C-1. We propose a mass assignment model to describe the specific heat capacity of nanocrystals, which divides it into four parts: electron, inner, surface, and ligand. By eliminating the contribution of ligand and electron specific heat capacity, the specific heat capacity of the inorganic core is linearly proportional to its surface-to-volume ratio, showing the size dependence. Based on this linear relationship, surface specific heat capacity accounts for 40-60% of the specific heat capacity of nanocrystals with size decreasing. It can be attributed to the uncoordinated surface atoms, which is evidenced by the appearance of extra surface phonons in Raman spectra and ab initio molecular dynamics (AIMD) simulations.

Manipulation of Macrophage Uptake by Controlling the Aspect Ratio of Graft Copolymer Micelles.

Nanostructures of drug carriers play a crucial role in nanomedicine due to their ability to influence drug delivery. There is yet no clear consensus regarding the optimal size and shape (e.g., aspect ratio) of nanoparticles for minimizing macrophage uptake, given the difficulties in controlling the shape and size of nanoparticles while maintaining identical surface properties. Here, we employed graft copolymer self-assembly to prepare polymer micelles with aspect ratios ranging from 1.0 (spherical) to 10.8 (cylindrical) and closely matched interfacial properties. Notably, our findings emphasize that cylindrical micelles with an aspect ratio of 2.4 are the least susceptible to macrophage uptake compared with both their longer counterparts and spherical micelles. This reduced uptake of the short cylindrical micelles results in a 3.3-fold increase in blood circulation time compared with their spherical counterparts. Controlling the aspect ratio of nanoparticles is crucial for improving drug delivery efficacy through better nanoparticle design.