Proceedings of the National Academy of Sciences

Lipid droplets (LDs) are dynamic organelles that regulate cellular lipid storage and mobilization through the coordinated action of LD-associated proteins. Patatin-like phospholipase domain-containing proteins PNPLA2 (ATGL) and PNPLA3 are central regulators of lipid metabolism, yet the molecular mechanisms underlying their membrane targeting and distinct enzymatic activities remain poorly understood. Here, we combine coarse-grained and all-atom molecular dynamics simulations with enhanced sampling to investigate how PNPLA2 and PNPLA3 associate with endoplasmic reticulum (ER) and LD membranes. Despite sharing a conserved N-terminal patatin domain, the two proteins exhibit distinct membrane-binding modes driven by divergent C-terminal amphipathic helices. In both proteins, membrane association is mediated primarily by deep insertion of C-terminal helices, while the patatin domain provides surface contact. PNPLA2 forms a deeply embedded U-shaped helical bundle on LDs that induce pronounced membrane curvature and promote opening of the catalytic dyad, consistent with its high triglyceride lipase activity. In contrast, PNPLA3 engages membranes through a more flexible helical arrangement that maintains a compact catalytic geometry and limits substrate accessibility. Membrane composition further modulates these interactions and leads to protein-specific lipid redistribution and curvature remodeling. Fluorescence microscopy experiments validate the computational predictions and demonstrate that mutation of a single arginine residue within the C-terminal region is sufficient to reduce LD targeting of both proteins. These results establish a mechanistic connection between membrane binding, conformational plasticity, and catalytic regulation in PNPLA2 and PNPLA3. Our work provides molecular insights into how lipid environments tune the function of LD-associated enzymes. Author SummaryLDs are essential cellular organelles that control how fats are stored and released, a process that relies on the precise recruitment and regulation of lipid-metabolizing enzymes. Our work focuses on two closely related enzymes, PNPLA2 (ATGL) and PNPLA3, which play central but distinct roles in lipid metabolism and metabolic diseases. Using a combination of multiscale modeling simulations and fluorescence microscopy, we examine how these proteins recognize and bind to ER and LD membranes. Although PNPLA2 and PNPLA3 share a conserved catalytic core, we show that they interact with membranes in different ways due to differences in their C-terminal amphipathic helices. We find that PNPLA2 forms a deeply embedded helical arrangement that reshapes the membrane and promotes access to its catalytic site, which explains why it typically shows strong lipase activity. In contrast, PNPLA3 adopts a more compact membrane-bound catalytic geometry that limits substrate access and enzymatic activity. We further applied fluorescence microscopy to experimentally validate the computational predictions. The results show that mutation of a single arginine residue within the membrane-binding helix reduces LD targeting. These findings reveal how membrane association and protein conformational dynamics jointly regulate catalytic accessibility and activity.

Violence against women is sustained not only by individual behavior but also by social norms that legitimize coercion and control. While attitudes justifying intimate-partner violence have been extensively documented in large-scale household surveys, they are rarely analyzed as structured, predictable population-level phenomena. Here, we model the continuous prevalence of violence-justifying attitudes across 70 countries and demographic subgroups using country-resolved supervised machine learning with strict out-of-sample evaluation. Drawing on harmonized estimates derived from the Demographic and Health Surveys, we quantify how much cross-subgroup variation in normative acceptance is explainable from survey structure alone. By comparing full models that incorporate attitudinal scenario framing with demographics-only baselines, we show that high predictability arises from fundamentally different sources across countries: in some contexts, demographic stratification--particularly education--structures normative acceptance, whereas in others, conditional justification narratives dominate. Integrating independent country-level indicators of gender inequality, human development, and democratic quality reveals that violence-justifying norms are most predictable in structurally polarized settings rather than within a single cultural regime. Together, these findings demonstrate that normative acceptance of violence is not uniformly diffuse but can form coherent, structurally embedded patterns. This cross-scale framework provides a quantitative basis for identifying where prevention strategies may benefit most from demographic targeting versus direct challenges to context-specific justifications of violence. Significance statementNormative acceptance of intimate-partner violence is a measurable societal risk factor, yet it is rarely analyzed as a structured population-level phenomenon. Most quantitative studies remain descriptive, and machinelearning analyses using large-scale household surveys typically focus on individual-level classification of victimization or vulnerability. Here, we model the continuous prevalence of violence-justifying attitudes across 70 countries and demographic subgroups using country-resolved supervised regression with rigorous out-of-sample evaluation. By contrasting demographics-only models with those incorporating attitudinal scenario framing, we show that cross-national differences in predictability arise from distinct sources--demographic stratification in some contexts and conditional justification narratives in others. Linking these patterns to independent indicators of gender inequality, human development, and democratic quality reveals that highly structured norms emerge in structurally polarized settings, highlighting where targeted prevention strategies are most likely to be effective.

Termites produce the most diverse array of terpenoids among metazoans, comprising over 200 structures. However, their biosynthesis has not yet been elucidated. Here, we identify a gene family which arose through the duplication of geranylgeranyl pyrophosphate synthase in the common ancestor of Neoisoptera, the terpene-producing termite lineage. We functionally characterized several proteins from this family as terpene synthases generating biologically relevant sesqui-and diterpenes. These include the queen pheromone (3R,6E)-nerolidol in Embiratermes neotenicus and the precursor of polycyclic defensive diterpenes (E,E,E)-neocembrene in Nasutitermes takasagoensis. We explore transposable element-mediated genomic mechanisms and selection pressures acting in the evolution of this gene family and report an amino acid site crucial for cyclization capacity as well as the enantiospecificity of the characterized enzymes. We conclude that we have identified an enzyme family underlying the remarkable richness of termite terpenoids, which likely contributed to the ecological success of Neoisoptera.

The alignment between mutational variance, standing genetic variance, and macroevolutionary divergence in Drosophila wing shape presents a rate paradox: evolution follows mutational lines of least resistance, yet proceeds orders of magnitude slower than quantitative genetic theory predicts. Two explanations have been proposed: "deleterious pleiotropy," where stabilizing selection on unmeasured traits outside the wing morphology complex constrains evolution, and "correlational selection," where selection acts directly on trait covariances. However, recent empirical work has found little evidence of fitness costs associated with wing shape variation beyond effects on flight performance, undermining the deleterious pleiotropy hypothesis. Here, I propose and evaluate a pleiotropic hitchhiking model, in which natural selection targets a single functional trait (wing size) while the complex geometry of wing veins evolves as a correlated response shaped by the structure of mutational variance. Using individual-based simulations parameterized with empirical mutational covariances, I show that univariate selection on a primary trait can reproduce the observed alignment among mutational variance, genetic variance, and divergence. Importantly, the pleiotropic hitchhiking model can also generate slower-than-neutral divergence rates, offering a resolution to the rate paradox without invoking hidden pleiotropic costs on unmeasured traits.

Individual differences in cognitive abilities have been linked to variability in cortical folding, a stable neuroanatomical scaffold largely established in utero. In the domain of reading, recent findings in small groups of typical readers suggest that a sulcal interruption (superficial annectant gyrus, gyral gap) in the left posterior occipital temporal sulcus (lhpOTS) predicts better reading skills, posing the lhpOTS as a potential early biomarker of reading difficulties. However, it remains unknown whether this relationship found in typical readers generalizes to the dyslexic population and whether the lhpOTS can serve as a biomarker for dyslexia or predict response to targeted instruction.To fill these gaps, we examine the patterns of the lhpOTS in 209 children, including children with dyslexia, from four independently-collected samples. In typical readers, we find that the relationship between the lhpOTS and reading skills is robust, replicating across binary and continuous quantifications of the sulcal interruption. However, lhpOTS patterns neither distinguish dyslexic children from typical readers nor do they predict response to intervention. Instead, targeted reading intervention drives long-term gains in reading skills that are equivalent irrespective of VOTC anatomy. Together, these findings distinguish neuroanatomical correlates of skilled reading from determinants of reading impairment and learning capacity and emphasize the importance of the educational environment in supporting reading acquisition for children with dyslexia. SIGNIFICANCE STATEMENTEarly predictors of dyslexia are important for understanding the etiology of reading difficulties and informing early intervention. One candidate biomarker for dyslexia is the left posterior occipital temporal sulcus (lhpOTS), a neuroanatomical feature established before birth. In typical readers, the presence of an interruption in the lhpOTS has been linked to better reading skills. Here, we examine this neuroanatomical feature in 209 children with and without dyslexia. While the lhpOTS reliably relates to reading skill in typical readers, it neither differentiates dyslexic from typical readers nor predicts response to intensive reading intervention. These results show that brain anatomy reflects reading proficiency but does not constrain learning and highlights the power of targeted intervention to support reading development.

Methyl-coenzyme M reductase (MCR) is the primary source of biogenic methane on Earth. In the active site of MCR, a nickel (Ni)-containing porphyrin (F430) must be in the Ni1+ oxidation state to initiate catalysis. The reductive activation of MCR, i.e., reduction of F430 to its Ni1+ state, is an ATP-dependent process, but the underlying ATPase and its precise role remain unknown. Component A2 is an ATP-binding protein that associates with MCR but, since it was reported to lack ATPase activity, its putative function was designated as an ATP-carrier protein. In contrast, recent structural insights into the MCR activation complex suggest that component A2 might hydrolyze ATP to drive conformational changes required for enzyme activation. Here, we provide direct biochemical evidence that component A2 is a bona fide ATPase that hydrolyzes ATP under strictly anaerobic conditions and only upon interaction with MCR. Mutational analyses reveal that component A2 must be bound to ATP prior to association with MCR and that residues involved in ATP hydrolysis do not impact protein-protein interaction. The two nucleotide-binding domains of A2 act cooperatively but display asymmetric contributions to ATP hydrolysis and MCR engagement. In addition, a distinctive N-terminal zinc-binding motif (ZBM) is required for maximal ATPase activity but is dispensable for MCR binding. Phylogenetic analyses reveal that this ZBM distinguishes component A2 from related ABC-type ATPases. Together, these findings identify component A2 as a distinct class of remodeling ATPases that powers conformational changes underlying the reductive activation of MCR. Significance StatementA large fraction of methane on Earth is generated by methanogenic archaea using the enzyme methyl coenzyme-M reductase (MCR). The maturation of MCR is a multi-step ATP-dependent process but the role of ATP and the corresponding ATPase(s) have remained unclear. Here, we show that component A2, a protein that is universally conserved in archaea that encode MCR and related enzymes, hydrolyzes ATP only upon interaction with MCR under anaerobic conditions. Our findings, together with recent structural studies, indicate that component A2-mediated ATP hydrolysis facilitates the reductive activation of MCR during the final step of its maturation. These results clarify a key step in the biogenesis of a central enzyme involved in biological methane production.

A novel class of protein misfolding, involving changes in entanglement status, occurs across the cytosolic proteome of a bacterium and likely occurs in many other organisms. Here, we examine if this class of misfolding has measurable downstream consequences for protein homeostasis. Specifically, we test the hypothesis that proteins that misfold in this way are more likely to be degraded by the ubiquitin-proteosome system immediately after synthesis. We do this by cross-referencing protein structural information with ubiquitin mass spectrometry (Ubq-MS) data from human fibroblast cells. Ubq-MS identifies proteins that have been covalently modified with ubiquitin in a particular pattern and is a cellular signal for that protein to be degraded by the proteosome. We find that nascent proteins with native entanglements, which were previously shown to be twice as likely to misfold, are 93% (95% Confidence Interval: [44%, 160%]) more likely to be tagged with ubiquitin and targeted to the proteasome compared to proteins that do not contain such entanglements. Simulating the folding of these proteins using a coarse-grained model, we find that the ubiquitin-tagged proteins containing native entanglements are four times more likely to misfold than the non-ubiquitinated proteins that are devoid of entanglements. These results indicate that entanglement misfolding, primarily involving a failure to form native entanglements, leads to an increased likelihood that those proteins will be degraded in human cells. Finally, we estimate that approximately one-third of the globular proteome likely misfolds in this way but bypasses proteasomal degradation because their misfolded states are structurally similar to their native ensemble. These consequences for protein degradation are likely common across organisms as entanglement misfolding is inherent to the polymeric nature of proteins.

Photosynthetic organisms in aquatic environments experience rapid fluctuations in light intensity, light quality, and carbon availability, requiring tight regulation of photosynthetic energy conversion. In marine diatoms, non-photochemical quenching (NPQ), particularly energy-dependent quenching (qE), plays a central role in dissipating excess excitation energy as heat. However, excessive NPQ can reduce photosynthetic efficiency under light-limiting or carbon-rich conditions, and how this trade-off is regulated remains poorly understood. Here, we identify CgLhcf9, a previously uncharacterized light-harvesting complex (LHC) protein, as a negative regulator of qE-type NPQ in the centric diatom Chaetoceros gracilis. Expression of CgLhcf9 is induced under low red-light and high CO2 conditions and strongly suppressed by blue light, indicating regulation by both light quality and carbon availability. Functional analyses using CgLhcf9 knockout and overexpression lines reveal that CgLhcf9 suppresses qE: NPQ induction is enhanced in the absence of CgLhcf9, whereas its accumulation downregulates NPQ without affecting other established qE effectors, including Lhcx1 or xanthophyll cycle pigments. Notably, CgLhcf9 accumulation improves cellular growth under light-limiting conditions. These results identify CgLhcf9 as a novel LHC-type regulator that fine-tunes photosynthetic energy dissipation in response to environmental signals. Our findings establish a regulatory mechanism that balances photoprotection, electron transport, and carbon fixation, advancing our understanding of how marine diatoms optimize photosynthesis under fluctuating light and CO2 conditions. Significance statementPhotosynthetic microalgae must balance light-driven electron transport with carbon fixation to maximize growth under fluctuating light and CO2 conditions. While non-photochemical quenching (NPQ) protects photosystems from excess light, excessive NPQ can limit photosynthetic efficiency when light or carbon is limiting. Here, we identify the antenna protein CgLhcf9 as a negative regulator of energy-dependent NPQ in the marine diatom Chaetoceros gracilis. CgLhcf9 integrates light-quality and CO2 signals to suppress NPQ without altering canonical quenching effectors, thereby improving growth under light-limiting conditions. This study reveals a regulatory role for a light-harvesting complex protein in tuning the balance between photoprotection and photosynthetic efficiency, providing insight into how marine diatoms coordinate electron transport and carbon fixation in dynamic environments.

Network oscillations in the gamma (30-80 Hz) frequency range are implicated in many vital neurological functions. The seminal Pyramidal Interneuron Network Gamma (PING) mechanism produces gamma oscillations in silico with dynamics associated with a strongly attracting limit cycle. However, this activity is stronger and more stable than what is observed during in vivo gamma oscillations, which are transient and driven by sparse spiking activity. Here we describe multiple biophysically motivated changes degenerately driving PING-motivated networks to produce more realistic gamma activity. Increased heterogeneity, synapse-like noise, and a depolarized chloride reversal potential each destabilize the attractor represented by PING-driven activity: minor alterations disrupt the unrealistic organization of idealized PING oscillations, while larger changes entirely prevent this overly-synchronous network activity. This allows new dynamics to emerge: spontaneous and transient increases in gamma-band oscillatory power with excitatory cells only weakly entrained to the population rhythm. These features, better approximating the in vivo reality, mirror a systems oscillatory return to a stable focus following noise-induced perturbations. In fact, dynamical systems with both a stable focus and limit cycle are associated with Hopf bifurcations, which have been characterized in models of reciprocally connected excitatory and inhibitory neuronal populations as required for PING. We therefore propose a revised explanation for physiologically-realistic gamma activity that retains the key elements of the PING mechanism--strong reciprocal connection between excitatory and inhibitory neurons--but where biophysical phenomena bias the system towards damped oscillations around a weakly stable focus rather than a stable limit cycle. Significance StatementThe mechanisms underlying network oscillations at gamma frequencies have long been a focus of computational neuroscience. This research has produced idealized mechanisms yielding highly synchronous, active, and stable oscillations; however, in vivo gamma rhythms are transient with sparse neuronal spiking. Here, we illustrate minimal, biophysically relevant adjustments to established Pyramidal Interneuron Network Gamma (PING) networks that bridge a major divide between these traditional in silico systems and the experimental reality. Uncorrelated noisy input and a depolarized chloride reversal potential disrupt stereotyped PING rhythms and promote more realistic transient increased gamma power in network activity. This important step forward in the modeling of gamma oscillations illustrates how including biophysical detail can promote more realistic activity in computational systems.

The COVID-19 pandemic led to substantial life expectancy losses globally. Historically, life expectancy reversals have been followed by rapid returns to previous trajectories, but whether this is true for the COVID-19 pandemic is still unknown. We update life expectancy estimates through 2024 for 34 high-income countries and quantify annual and cumulative life expectancy "deficits" by comparing observed life expectancy with counterfactuals based on pre-pandemic trends. Five years after the pandemics onset, recovery remains incomplete in most countries. In 2024, 31 out of 34 countries still had lower life expectancy than expected. Across 2020-2024, cumulative deficits were statistically significant in nearly all countries. We identify four distinct life expectancy trajectories: (a) first wave peak (largest deficits in 2020 with gradual recovery); (b) second wave peak (largest deficits in 2021 with a sharper rebound); (c) late peak (minimal early impact followed by smaller deficits from 2022 onward); (d) prolonged depression (smaller but persistent deficits without a sharp peak). In general, countries with severe second-wave peaks (such as the USA and Bulgaria) had the largest cumulative deficits. In contrast, countries that delayed widespread infection (e.g., Norway, Japan) saw later deficits that persisted through 2024, but with lower cumulative mortality. Our findings suggest that COVID-19 was not a uniform, short-lived mortality shock. Instead, most high-income countries experienced multi-year disruptions to life expectancy trajectories, with variable patterns of recovery that continue to shape population health five years on.

1.Space weather exerts profound effects on Earths technological systems, yet its influence on the terrestrial biosphere remains largely unexplored at the global scale. Despite decades of research on solar-terrestrial interactions, most studies have focused on technological and atmospheric effects, while potential influences on biological regulation remain largely unexplored. While local experiments suggest magnetic sensitivity in plants (Galland and Pazur 2005; Belyavskaya 2004), observational evidence for a planetary-scale vegetative response to geomagnetic disturbances is lacking. In particular, it is unclear whether weak and intermittent geomagnetic disturbances can leave detectable signatures in ecosystem-scale physiological processes. Here, we analyze a decade of satellite-derived solar-induced chlorophyll fluorescence (SIF) data alongside geomagnetic indices to isolate non-seasonal physiological anomalies. Using temperature-stratified cumulative correlation analysis and multivariate models controlling for radiative and hydrological drivers, we identify a robust, cumulative, and thermally gated association between geomagnetic activity and vegetation fluorescence. We report a global-scale coherent modulation of photosystem balance, potentially inferred from the SIF757/SIF771 ratio, with recurrent geomagnetic disturbances, exhibiting maximal coherence under cold and moderate thermal conditions and weakening under Optimum and Warm Stress regimes. This response intensifies with increasing integration window length, indicating progressive physiological integration of repeated perturbations. Comparative analyses demonstrate that geomagnetic forcing is frequently comparable to or exceeds major climatic drivers in explaining fluorescence variability within biologically active regimes. We propose a mechanism consistent with magnetic modulation of radical pair spin dynamics in iron-sulfur clusters and cryptochromes, potentially influencing reactive oxygen species generation and redox-regulatory adaptation. Our findings suggest that plants have evolutionarily co-opted geomagnetic variability as an informational signal, integrating it into existing redox-regulatory networks. Rather than a passive mechanical perturbation, the observed response reflects an evolved sensitivity that operates near physiological criticality--a hypothesis that opens new frontiers in understanding magnetosphere-biosphere coupling.

Carboxysomes are bacterial microcompartments that drive efficient carbon fixation in autotrophic bacteria. Critical to their function and inheritance is their spatial organization by the ParA-type ATPase, McdA, and its partner protein, McdB. Here, we investigate the -carboxysome McdAB system in Halothiobacillus neapolitanus using biochemical assays, quantitative fluorescence imaging, and mathematical modeling. We find that, unlike most ParA-type ATPases, the ATPase activity of McdA is only stimulated by DNA rather than by its partner protein McdB. Despite this difference, McdB conserves the ability to displace McdA from DNA, suggesting that ATP hydrolysis and DNA unbinding by McdA are not strictly coupled. Together with its ability to diffuse while bound to DNA, McdA forms gradients on the nucleoid that prevent carboxysome aggregation via a Brownian ratchet mechanism. Overall, these findings reveal key differences in a ParA-type ATPase that may be specific for the spatial organization of protein-based organelles in bacteria.

Membrane association of intrinsically disordered proteins (IDPs) mediates various cellular functions including membrane remodeling and signal transduction. Whereas membrane association through amphipathic helices and polybasic motifs is well understood, sequence determinants for deep membrane insertion of aromatic residues are still poorly characterized. Here, we decipher the sequence code for membrane insertion of aromatic-centered motifs. For an initial set of 10 9-residue aromatic-centered sequences, all-atom molecular dynamics simulations and the positioning of proteins in membranes (PPM) method produced very similar membrane insertion propensities. Applying PPM to a full library of 1.2 x 106 sequences with an F, W, or Y residue flanked by L, R, G, N, or E at four positions on either side, we found that aliphatic (L) and basic (R) residues favor membrane insertion, whereas acidic (E) and polar (N) residues disfavor it. Guided by these rules, we developed a mathematical model dubbed AroMIP to predict the membrane insertion propensities of aromatic-centered motifs. AroMIP achieves 91.2%, 92.0%, and 99.7% accuracies for F-, W-, and Y-centered motifs, respectively, in disordered regions of the human proteome and is available as a web server at https://zhougroup-uic.github.io/AroMIP/. The present work provides the sequence basis and a mechanistic understanding of how IDPs employ aromatic-centered motifs to drive membrane insertion, and enriches the tools for the study of IDP-membrane association. Significance StatementMembrane insertion of short motifs, along with membrane tethering of amphipathic helices and membrane binding of polybasic motifs, is a major mode of membrane association and mediates diverse functions including membrane remodeling and signal transduction. Here we used three complementary approaches to decipher the sequence code of membrane insertion, culminating in a sequence-based method, AroMIP, for predicting membrane-insertion propensities. Aromatic sidechains have the intrinsic ability to insert deeply into the acyl chain region of membranes; at flanking positions, they strongly stabilize the inserted state. Aliphatic and basic residues are medium to modest promoters of membrane insertion. AroMIP has >90% accuracy and identifies important motifs for regulating functions of intrinsically disordered proteins via membrane insertion.

Understanding how intrinsic brain dynamics are organized is critical for explaining human cognition and sensory processing. Theoretical frameworks propose a hierarchical architecture in which some neural systems act as orchestrators, broadcasting information across the brain, whereas others serve as integrators, transforming incoming signals. Here, we quantitatively test whether this orchestration-integration framework is embedded in intrinsic brain activity, that is, in the absence of explicit cognitive/sensorial tasks. We adopt a multivariate fractional modeling framework originally developed in financial mathematics to characterize how volatility propagates across interacting markets, thereby identifying systems that act as orchestrators or integrators. We then test whether this integrator-orchestrator axis is related to human intelligence. To this end, using 7T resting-state functional magnetic resonance imaging data from 173 healthy young adults, we model spontaneous brain fluctuations with a multivariate fractional Ornstein-Uhlenbeck process to derive directional influence indices. Consistent with our predictions, we identified a bipartite organization, stable across modeling choices. At the subcortical level, the anterior thalamus, putamen, and caudate emerged as orchestrating transmitters, whereas the posterior thalamus, globus pallidus, hippocampus, amygdala, and nucleus accumbens acted as integrating receivers. At the cortical level, attentional and sensory networks functioned as orchestrating transmitters, while higher-order cognitive networks served as integrating receivers. These findings provide support for a theoretically grounded integration-orchestration framework, demonstrating that brain signaling is organized along this axis even at rest, relevant for intelligence scores. The proposed fractional framework offers a principled tool to investigate how disruptions of this balance may contribute to brain disorders. Competing Interest StatementNone.

Having at least one of the small soluble electron carriers cytochrome c6 (c6) and plastocyanin is indispensable for photosynthesis. It was believed that c6 had been lost from plants until the identification of a ubiquitous and highly conserved homologue, now named cytochrome c6A (c6A), led to a paradigm shift. However, c6A was soon shown to be unable to replace c6 (or plastocyanin) functionally in the photosynthetic electron transport chain, despite their significant structural homology. The function of c6A, and why it is apparently universal in plants and green algae, remain unknown. Here, we show that, in the green alga Chlamydomonas reinhardtii, c6A confers a growth advantage under fluctuating light and is crucial for maintaining the light harvesting balance between photosystems I and II in photomixotrophic conditions. We show that in the absence of c6A, the light harvesting balance shifts towards PSII, leading to a more reduced plastoquinone pool and increased photooxidative stress. This study provides new insights into how photosynthetic organisms acclimatize to stressful light conditions, indicating that c6A is important for this adaptation. These findings provide a basis for further mechanistic studies on a hypothesized role for c6A in thiol-based redox regulation in the thylakoid lumen, with implications for photoprotection mechanisms such as state transitions.

The bacterial actin homologue MreB plays a key role in rod cell shape determination. We recently showed that MreB from the Gram-positive bacterium Geobacillus stearothermophilus (MreBGs) polymerizes into straight pairs of protofilaments in the presence of both ATP and a lipid surface. Membrane interaction is thought to be mediated by electrostatic interactions with anionic lipids, with final anchoring relying on two spatially close hydrophobic motifs that protrude from the MreBGs monomers, forming a putative membrane-insertion domain. Here, we determined the binding properties of ATP and ADP to MreBGs using fluorescence anisotropy, and monitored ATP-mediated binding and polymer formation on lipid bilayers using liposome binding assays and AFM, respectively. Finally, we used solid-state NMR to visualize the interaction between the membrane and MreBGs at the atomic level. Our findings reveal that MreBGs has similar affinity for both ATP and ADP, unlike eukaryotic actin. We also show that monomeric MreBGs establishes peripheral contacts with the membrane likely through electrostatic interactions, while ATP-induced MreBGs filaments insert into the lipid bilayer without interfering with the membrane lamellar phase and have a significant local fluidifying effect. Statement of significanceBacteria rely on the actin-like protein MreB to determine and maintain their cell shape, like actin does in eukaryotic cells. To perform its tightly regulated morphogenetic function, MreB forms membrane-associated nanofilaments in vivo, which control the cell wall biosynthetic machinery. We recently demonstrated that, in vitro, MreB from the Gram-positive bacterium Geobacillus stearothermophilus requires both ATP and lipids to polymerize into pairs of filaments. Here, we show that in the presence of ATP, Geobacillus MreB forms membrane-bound filaments that directly impact local membrane fluidity, which could translate into a regulatory effect on cell wall synthetic enzymes. We further reveal that MreB binds both ATP and ADP with similar affinity, unlike eukaryotic actin, which preferentially binds ATP over ADP, and speculate that this could be a mechanism modulating the pool of polymerization-competent MreB in bacteria.

How the human brain organizes complex cognitive functions remains unresolved, particularly regarding the debate between localized and distributed architectures. Here, we show that the language network undergoes a non-linear developmental reorganization that reconciles these views. Using multimodal neuroimaging and behavioral measures, we identify a three-stage trajectory: early localization, a transiently distributed state during adolescence marked by a connectivity dip, and a return to refined localization in adulthood. This adolescent dip is behaviorally meaningful and contributes to integrative network architecture. Convergent shifts in functional connectivity and brain-behavior relationships identify adolescence as a critical window for large-scale network remodeling. Our findings provide a unifying framework for language network development and suggest that transient redistribution may represent a general principle of human brain maturation.

Robust evidence now suggests that numerosity perception emerges from the early visual cortex. However, such empirical findings pose a theoretical challenge for explaining how a low-level perceptual system represents discrete values from continuous input independently of other magnitude dimensions. Among proposals for this representational invariance, two computational accounts with ties to neural data have garnered attention: divisive normalization and Fourier decomposition. Here, we test these hypotheses using an integrated neural, behavioral, and computational approach and show that: (1) The visual cortex remains sensitive to numerosity even when the input images are equalized for their Fourier power, inconsistent with the Fourier decomposition account. (2) The divisive normalization model explains this neural phenomenon through the selective disruption of fine but not coarse visual channels when encoding normalized local contrast. (3) Backward masking that disrupts fine processing in a psychophysical experiment degrades the acuity of intact dot arrays to the level of Fourier-power equalized dot arrays, which validates the unique prediction of the divisive normalization model. These findings provide converging evidence for the proposal that normalized local contrast enables representational invariance of numerosity in the visual cortex.

A recently discovered class of protein misfolding involving native entanglements could be a widespread mechanism by which loss-of-function diseases arise. Here, we test that hypothesis by examining if there is any statistical association between proteins predisposed to misfold in this way and a database of gene-disease relationships. We find that globular proteins containing non-covalent lasso entanglements (NCLEs) in their native structure, which are more prone to misfolding, are 61% more likely to be associated with disease, 68% more likely to harbor pathogenic missense mutations, and their misfolding-prone entangled regions are 64% more likely to harbor pathogenic missense mutations. Protein refolding simulations indicate that these disease associated, natively entangled proteins are 2.5-times more likely to misfold than comparable non-disease proteins that lack native NCLEs. These results indicate that native entanglement misfolding, especially in the presence of missense mutations, have the potential to contribute to a wide variety of diseases. More broadly, these findings open an entirely new space of therapeutic targets in which drugs are designed to avoid these misfolded states and increase the amount of folded, functional protein.

Changes in intracellular pH are critical for maintaining homeostasis, mediating signaling pathways, and enabling cellular responses to stress, injury, and disease. There is increasing evidence that clusters of acidic residues, primarily glutamates, are both highly prevalent and conserved in disordered regions of proteins and can play an important role in cellular pH response. Tubulin C-terminal tails (CTTs) are glutamate rich regions which protrude from the microtubule surface. These tails are a primary site of for both post-translational modifications and binding of microtubule-associated proteins. Motivated by these observations, we measured the pH response of tubulin CTTs using NMR spectroscopy, circular dichroism, and computational simulations. We find that glutamate residues in CTTs taken from organisms across eukaryotes exhibit a robust upshift in their pKa values, that the sequential context of glutamate residues creates hot spots for protonation, and that hydrogen bonding between side chains stabilizes interactions that alter the conformation of the CTT. To determine whether the CTT pH response plays a potentially important role in microtubule interactions, we measured the pH dependence of the binding of the yeast kinesin-5, Cin8, to microtubules. We find that Cin8 binding is modulated by pH in a CTT-dependent manner. Our results demonstrate that acidic clusters are important mediators of cellular pH response and establish that pH can regulate interactions at the microtubule surface. Significance StatementVariation in cellular pH is important for cell function in changing environmental conditions or developmental states. Here we probe protonation of the glutamate-rich C-terminal tails of tubulin, revealing the existence of and mechanism driving the anomalously high pH response and subsequent regulation of microtubule binding. Our results demonstrate that acidic clusters are important mediators of cellular pH response and establish pH-based regulation of interactions at the microtubule surface.