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RAD51AP1 is a versatile RAD51 modulator
RAD51AP1 is an emergent key factor in homologous recombination (HR), the major pathway for accurate repair of DNA double-strand breaks, and in alternative lengthening of telomeres (ALT). Depletion of RAD51AP1 diminishes HR and overexpression is common in cancer, where it is associated with malignancy. Here, we show that RAD51AP1 has a hitherto unknown role in modulating the RAD51 recombinase, the central player in HR. Through a combination of biochemistry and structural biology, we reveal that RAD51AP1 possesses at least three RAD51-binding sites that facilitate its binding across two adjacent RAD51 molecules. We uncover a previously unidentified RAD51-binding mode that stabilizes the RAD51 N-terminal domain and protomer interface in the filaments. We uncover a previously undescribed role for RAD51AP1 in stabilizing RAD51-ssDNA filaments and promoting strand exchange. Our structural data provide the molecular basis for how RAD51AP1 binding induces conformational changes that promote RAD51 DNA association and oligomerization, therefore promoting filament nucleation, stabilization, and strand exchange. Further, we resolved structures of RAD51-ssDNA filaments in the presence of Mg 2+ -ATP and upon hydrolysis to Mg 2+ -ADP, revealing that RAD51 filaments expand upon ATP hydrolysis and explaining how ADP reduces RAD51–DNA binding. Our findings reveal RAD51AP1 as a versatile RAD51 modulator and RAD51 filament remodeler and shed previously unidentified insights into the modulation of HR, which is critical for the maintenance of genome stability.
Flow cytometry-based targeted diagnostics for rapid assessment of daunorubicin resistance in acute myeloid leukemia
Abstract Acute myeloid leukemia (AML) is an aggressive hematologic malignancy where chemoresistance, particularly to daunorubicin (DNR), frequently leads to treatment failure and relapse. Current resistance prediction methods are often slow and inaccessible in clinical settings, delaying crucial treatment adjustments. There is an urgent need for rapid, reliable, and clinically accessible diagnostic tools to identify DNR resistance early, enabling personalized therapeutic strategies and improving patient outcomes. To address this problem, we developed a rapid flow cytometric assay to detect reduced intracellular DNR accumulation, a marker of drug resistance. This was complemented by FTIR spectroscopy, confocal microscopy, and proteomic profiling to validate findings and explore underlying mechanisms in drug-resistant and sensitive cells. The flow cytometry method demonstrated that the novel Sensitivity Index (S-index) accurately predicts DNR resistance after short drug exposure and correlates strongly with IC 50 values. Complementary FTIR and confocal microscopy revealed distinct biochemical and structural differences between resistant and sensitive cells. Proteomic analysis suggests that increased drug metabolism contributes to DNR resistance, supporting the flow cytometry data. In summary, our findings demonstrate that flow cytometry provides a reliable and clinically accessible tool for targeted diagnostics, crucial for optimizing patient-specific treatment strategies based on rapid assessment of daunorubicin resistance in AML.
Dynamic changes in chloride homeostasis coordinate midbrain inhibitory network activity during reward learning
Cryogenic light microscopy of vitrified samples with angstrom precision
High-resolution studies in structural biology are often limited by the challenges of crystallization and low contrast in the cellular native environment. The exquisite labeling specificity of fluorescence microscopy gets around these issues and allows superresolution microscopy, but to date, these works have used chemically fixed samples. To establish light microscopy as a workhorse in structural biology, two main requirements must be fulfilled: near-native sample preservation and near-atomic optical resolution. Here, we introduce single-particle cryogenic light microscopy (spCryo-LM) as a technique that satisfies these key criteria. We adapt established protocols from cryogenic electron microscopy (Cryo-EM) for shock-freezing samples and use a high-vacuum cryogenic shuttle system to transfer them in and out of a liquid-helium cryostat that houses a superresolution fluorescence microscope. By exploiting the enhanced photophysics at low temperature, angstrom precision can be achieved in localizing several fluorophores attached to proteins separated by a few hundred nanometers. We present various characterization studies on vitreous ice, single-molecule photoblinking behavior, and the effects of laser intensity and benchmark our method by resolving the heptameric membrane protein alpha-hemolysin in a synthetic lipid membrane. Additionally, we report on the technique’s capability to resolve membrane proteins in their native cellular membrane environment. spCryo-LM enables structural studies of proteins in their native environment without chemical fixation or protein isolation, and can be integrated with other superresolution or spectroscopic techniques. We believe our approach establishes light microscopy as a powerful tool in structural biology and sets the stage for correlative microscopy with Cryo-EM and related techniques.
Rumination catastrophism and pain in injured athletes
Primary material supply configurations and domestic recycling for cost-effective battery material production in the US
Abstract Battery cathode active material costs hinge on regionally concentrated, price-volatile metal supply. Here. we construct a regional facility-level cost model based on over 80 global lithium, cobalt, and nickel mines, refineries, and battery-grade material plants. Our model yields aggregated lithium, nickel, manganese, and cobalt production material costs from 392 region-based supply configurations for five different cathode active materials. Focusing on the United States, all-domestic supply is 9–34% costlier than global average, increasing by cobalt content, while these shortfalls can be overcome by selective low-cost material imports. Furthermore, we analyze costs of two U.S.-based recycling facilities from primary data and techno-economic modelling and compare resulting cathode active material-level costs to primary supply. Although it is still significantly higher on cathode active material cost-level, rising end-of-life flows and lowered black-mass prices will, however, make secondary supply cost-competitive to domestic and foreign primary supply cost floors. Facility-level benchmarks reveal targeted import, scaling, and production cost optimization as levers for a resilient, cost-effective U.S. battery-material supply chain.
Erasable serum markers
Gene expression in the brain is typically evaluated using invasive biopsy or postmortem histology. Serum markers provide an alternative way to monitor the brain, but relatively few such markers exist. Additionally, the origin of serum markers often cannot be localized to a specific cell population, and monitoring dynamic changes in their gene expression is compromised by the same factor that makes the markers detectable—long serum half-life. Here, we propose a paradigm to improve the sensitivity of serum marker measurement by modifying them with an external chemical stimulus. As a proof of concept, we use a well-controlled system with known half-life and tunable serum levels. This system, released markers of activity (RMA), or RMAs enables measurement of transgene expression in the brain through a simple blood test. RMAs are stable in blood, with a half-life of >100 h and can detect expression from as few as 12 neurons in mice. However, their long serum half-life also generates detectable background signals when RMA are used to track temporal changes in gene expression. By engineering on-demand erasable RMAs and injecting an intravenous targeted protease, we reduced RMA background signal by more than an order of magnitude without compromising the detection sensitivity. Similarly to previous RMA iterations, our approach showed a 65,000-fold increase in their signal over the baseline when expressed in a single brain region but also improved the dynamic range of detection for low-level promoter activity that is driven by physiological levels of c-Fos.
Nutritional management of Carpoglyphus lactis diets enhances Amblyseius swirskii performance for biological control
Chemically modified CRISPR-Cas9 enables targeting of individual G-quadruplex and i-motif structures, revealing ligand-dependent transcriptional perturbation
Abstract The development of selective ligands to target DNA G-quadruplexes (G4s) and i-motifs (iMs) has revealed their relevance in transcriptional regulation. However, most of these ligands are unable to target individual G4s or iMs in the genome, limiting their scope. Herein, we describe an Approach to Target Exact Nucleic Acid alternative structures (ATENA) that relies on the chemical conjugation of established G4 and iM ligands to a catalytically inactive Cas9 protein (dCas9), enabling their individual targeting in living cells. ATENA demonstrates that the selective targeting of the G4 present in the oncogene c-MYC leads to the suppression of transcripts regulated exclusively by one of its promoters (P1). Conversely, targeting the c-MYC iMs on the opposite strand leads to the selective increase of P1-driven transcripts. ATENA reveals that G4-mediated transcriptional responses are highly ligand-specific, with different ligands eliciting markedly different effects at the same G4 site. We further demonstrate that the basal expression levels of the gene targeted can be used to predict the transcriptional impact associated with G4-stabilization. Our study provides a platform for investigating G4- and iM-biology with high precision, unveiling the therapeutic relevance of individual DNA structures with selectivity.
Global stability of epidemic models with uniform susceptibility
Transmission dynamics of infectious diseases are often studied using compartmental mathematical models, which are commonly represented as systems of autonomous ordinary differential equations. A key step in the analysis of such models is to identify equilibria and find conditions for their stability. Local stability analysis reduces to a problem in linear algebra, but there is no general algorithm for establishing global stability properties. Substantial progress on global stability of epidemic models has been made in the last 20 y, primarily by successfully applying Lyapunov’s method to specific systems. Here, we show that any compartmental epidemic model in which susceptible individuals cannot be distinguished and can be infected only once, has a globally asymptotically stable (GAS) equilibrium. If the basic reproduction number R 0 satisfies R 0 > 1 , then the GAS fixed point is an endemic equilibrium (i.e., constant, positive disease prevalence). Alternatively, if R 0 ≤ 1 , then the GAS equilibrium is disease-free. This theorem subsumes a large number of results published over the last century, strengthens most of them by establishing global rather than local stability, avoids the need for any stability analyses of these systems in the future, and settles the question of whether coexisting stable solutions or nonequilibrium attractors are possible in such models: They are not.
Exploring the gap between theory and experiment at the three-phase contact line of polystyrene droplets on soft PDMS
Abstract The shape of liquid polystyrene (PS) droplets obtained via the dewetting of nanometer thin PS films from soft viscoelastic polydimethylsiloxane (PDMS) substrates are investigated. For a range of droplet sizes and substrate elasticities we measure the profiles of all the interfaces by combining lift-off techniques with atomic force microscopy and compare them to the predictions of fully time-dependent sharp-interface models for the PS/PDMS system, that are derived through energy minimization methods and allow to follow the dewetting dynamics towards their equilibrium states. Our analysis shows that there is a thin layer of uncrosslinked PDMS molecules that cloaks the PS droplets. By incorporating the effect of cloaking into the surface energies of our theoretical model, the experimental droplet and substrate profiles are shown to be in excellent quantitative agreement for all considered droplet sizes and substrate elasticities. Interestingly, our comparisons also establish small but systematic discrepancies between the experimental results and the theoretical predictions in the vicinity of the three-phase contact line. These discrepancies tend to increase for softer substrates and smaller droplets. Our analysis shows that global variations in system parameters, such as surface tension and elastic shear modulus, cannot account for these differences but instead point to a locally larger elastocapillary length, whose possible origins we investigate in detail.
Implementing N-terminomics and machine learning to probe Nt-arginylation
Large role of anthropogenic climate change in driving smoke concentrations across the western United States from 1992 to 2020
Wildfire activity has increased dramatically in the western United States over the last three decades, having a significant impact on air quality and human health. However, quantifying the drivers of trends in wildfires and subsequent smoke concentrations is challenging, as both natural variability (NV) and anthropogenic climate change (ACC) play important roles. Here, we devise an approach involving observed meteorology and vegetation and a range of models to determine the relative roles of ACC and NV in driving burned area across the western United States. We also examine the influence of ACC on smoke concentrations. We estimate that ACC accounts for 33 to 82% of observed total burned area, depending on the ecoregion, yielding 65% of total fire emissions on average across the western United States from 1992 to 2020. In all ecoregions except Mediterranean California, ACC contributes to a greater percentage of burned area in lightning-ignited wildfires than in human-ignited wildfires. On average, ACC contributes 49% to smoke PM 2.5 concentrations in the western United States from 1997 to 2020, and explains 58% of the increasing trend in smoke PM 2.5 from 2010 to 2020. Northern California and areas in Oregon, Washington, and Idaho experience the greatest smoke concentrations attributable to ACC, averaging 40 to 66% of total PM 2.5 over 2010–2020. Our work highlights the significant role of ACC in degrading air quality in the western United States and identifies those regions most vulnerable to wildfire smoke and thus adverse health impacts.
Joint energy-aware task offloading and privacy protection in healthcare monitoring systems via deep reinforcement learning
An astrocytic ensemble at vHip-NAc synapses modulates cognitive impairments induced by chronic tetrahydrocannabinol exposure
Core microRNAs regulate neural crest delamination and condensation in the developing trigeminal ganglion
Cranial neural crest cells (NCCs) undergo dynamic processes during embryonic development, including delamination from the neural tube by epithelial-to-mesenchymal transition (EMT), migration to the periphery, condensation via mesenchymal-to-epithelial transition (MET), and differentiation into structures like the trigeminal ganglion. Here, we identify and characterize the function of a core set of miRNAs involved in these transitions during the formation of the trigeminal ganglion in the chick embryo. We further identify putative targets of miRNAs involved in neural crest EMT and MET. Notably, introducing MET-involved miRNAs into trunk NCCs endows these cells with the ability to condense and differentiate into neurons in vivo in a manner reminiscent of cranial rather than trunk NCCs. Our findings shed light on the intricate regulatory networks governing NCC behavior, positioning miRNAs as key regulatory elements required for migratory transitions and axial level–specific differentiation capabilities.
Estimation of undetected asymptomatic infections of COVID-19: a mathematical modeling approach
State-space kinetic Ising model reveals task-dependent entropy flow in sparsely active nonequilibrium neuronal dynamics
Abstract Neuronal ensemble activity, including coordinated and oscillatory patterns, exhibits hallmarks of nonequilibrium systems with time-asymmetric trajectories to maintain their organization. However, assessing time asymmetry from neuronal spiking activity remains challenging. The kinetic Ising model provides a framework for studying the causal, nonequilibrium dynamics in spiking recurrent neural networks. Recent theoretical advances in this model have enabled time-asymmetry estimation from large-scale steady-state data. Yet, neuronal activity often exhibits time-varying firing rates and coupling strengths, violating the steady-state assumption. To overcome this limitation, we developed a state-space kinetic Ising model that accounts for nonstationary and nonequilibrium properties of neural systems. This approach incorporates a mean-field method for estimating time-varying entropy flow, a key measure for maintaining the system’s organization through dissipation. Applying this method to mouse visual cortex data revealed greater variability in causal couplings during task engagement despite reduced neuronal activity with increased sparsity. Moreover, higher-performing mice exhibited increased coupling-related entropy flow per spike during task engagement, suggesting more efficient computation in the higher-performing mice. These findings underscore the model’s utility in uncovering intricate asymmetric causal dynamics in neuronal ensembles and linking them to behavior through the thermodynamic underpinnings of neural computation.
The human endogenous retroviral envelope HEMO protein interacts with BACE2: Novel partnership acquired in the primate lineage
Endogenous retroviruses (ERV) represent 8 to 10% of mammalian genome. While most ERV are defective, a few retroviral genes, such as the envelope syncytins, were exapted during evolution and likely contributed to the emergence of placental mammals. We have previously identified the oldest full-length retroviral envelope gene in the human genome, HEMO (Human Endogenous MER34 ORF), endogenized in an ancestral mammal approximately 100 Mya. The transmembrane HEMO protein is predominantly expressed in the placenta and solid tumors. It is unexpectedly secreted from the cell surface as a soluble SHED form which can be detected in pregnant women blood. HEMO is nonfusogenic, having lost both its furin cleavage site between the SU and TM subunits, and its fusion peptide. To identify a potential receptor or partner of HEMO, we developed an original strategy leveraging the fusogenic property of the Measles virus proteins to screen a human ORFeome expression library by cell–cell fusion. We successfully identified the transmembrane aspartic protease BACE2 (ß-site APP-cleaving enzyme 2) as a specific interacting partner for both SHED and transmembrane HEMO proteins. We further determined the emergence time of this interaction, using in silico reconstructed ancestral “HEMO” sequences from several mammals. We identified two specific point mutations—resulting in two new cysteines in close proximity and loss of the SU-TM furin cleavage of HEMO—that appeared in the simian catarrhine lineage 30 to 45 Mya, and enabled interaction of this ancestral primate HEMO with BACE2, possibly for another physiological function prolonging HEMO conservation for tens of millions of years until humans.