eLife最新文献

Motility endows microorganisms with the ability to swim to nutrient-rich environments, but many species are sessile. Existing hydrodynamic arguments in support of either strategy, to swim or to attach and generate feeding currents, are often built on a limited set of experimental or modeling assumptions. Here, to assess the hydrodynamics of these 'swim' or 'stay' strategies, we propose a comprehensive methodology that combines mechanistic modeling with a survey of published shape and flow data in ciliates. Model predictions and empirical observations show small variations in feeding rates in favor of either motile or sessile cells. Case-specific variations notwithstanding, our overarching analysis shows that flow physics imposes no constraint on the feeding rates that are achievable by the swimming versus sessile strategies - they can both be equally competitive in transporting nutrients and wastes to and from the cell surface within flow regimes typically experienced by ciliates. Our findings help resolve a long-standing dilemma of which strategy is hydrodynamically optimal and explain patterns occurring in natural communities that alternate between free swimming and temporary attachments. Importantly, our findings indicate that the evolutionary pressures that shaped these strategies acted in concert with, not against, flow physics.

Functional MRI (fMRI) research has traditionally investigated task processing using static blocked or event-related designs. Consequently, our understanding of threat processing remains limited to findings from paradigms with restricted dynamics. In this paper, we applied switching linear dynamical systems (SLDSs) to uncover the dynamics of threat processing during a continuous threat-of-shock paradigm. Unlike typical systems neuroscience studies that assume systems are decoupled from external inputs, we characterized both endogenous and exogenous contributions to the dynamics. We first demonstrated that the SLDS model learned the regularities of the experimental paradigm; states and state transitions estimated from fMRI data across 85 regions of interest reflected both threat proximity and direction (approach vs. retreat). After establishing that the model captured key properties of threat-related processing, we characterized the dynamics of states and their transitions. The results reveal how threat processing can be viewed as dynamic multivariate patterns whose trajectories are determined by intrinsic and extrinsic factors that jointly drive how the brain temporally evolves. Furthermore, we developed a measure of region importance to quantify individual brain region contributions to system dynamics, complementing the system-level SLDS formalism. Finally, we demonstrated that an SLDS model trained on one paradigm successfully generalizes to a separate experiment, capturing fMRI dynamics across distinct threat-processing tasks. We propose that viewing threat processing through the lens of dynamical systems offers vital avenues to uncover properties of threat dynamics not unveiled by standard experimental designs.

Despite the growing public health threat of electronic cigarettes (e-cigs), the cell-specific immune responses to differently flavored e-cig exposure remain poorly understood. To bridge this gap, we characterized the lung immune landscape following acute nose-only exposure to flavored e-cig aerosols in vivo using single-cell RNA sequencing (scRNA seq) in mice. Metal analysis of daily generated aerosols revealed flavor-dependent, day-to-day variation in metal (Ni, Cu, K, and Zn) leaching. scRNA seq profiling of 71,725 lung cells from control and exposed mice revealed pronounced dysregulation of myeloid cell function in menthol (324 differentially expressed genes, DEGs) and tobacco (553 DEGs) flavors, and lymphoid cell dysregulation in fruit-flavor (112 DEGs) e-cig aerosol exposed mouse lung, compared to air controls. Flow cytometry corroborated these findings, showing increased neutrophil frequencies and reduced eosinophil counts in menthol- and tobacco-exposed lungs. Flavored e-cig exposure also increased CD8⁺ T-cell proportions, upregulated inflammatory gene expression (Stat4, Il1b, Il1bos, Il1ra, and Cxcl3), and enriched terms like 'Th1 cytokine signaling' and 'NK cell degranulation'. Notably, tobacco-flavored e-cig aerosol exposure increased immature (Ly6G⁻) neutrophils and reduced S100A8 expression, suggesting altered neutrophil activation in vivo. Overall, this study identifies flavor-dependent immune alterations in the lung following acute e-cig aerosol exposure and provides a foundation for future mechanistic studies.

The rapid and sustained proliferation of cancer cells necessitates increased protein production, which, along with their disrupted metabolism, elevates the likelihood of translation errors. Ribosome-associated quality control (RQC), a recently identified mechanism, mitigates ribosome collisions resulting from frequent translation stalls. However, the precise pathophysiological role of the RQC pathway in oncogenesis remains ambiguous. Our research centered on the pathogenic implications of mitochondrial stress-induced protein carboxyl-terminal alanine and threonine tailing (msiCAT-tailing), a specific RQC response to translational arrest on the outer mitochondrial membrane, in human glioblastoma multiforme (GBM). The presence of msiCAT-tailed mitochondrial proteins was observed commonly in glioblastoma stem cells (GSCs). The exogenous introduction of the mitochondrial ATP synthase F1 subunit alpha (ATP5α) protein, accompanied by artificial CAT-tail mimicking sequences, enhanced mitochondrial membrane potential (ΔΨm) and inhibited the formation of the mitochondrial permeability transition pore (MPTP). These alterations in mitochondrial characteristics provided resistance to staurosporine (STS)-induced apoptosis in GBM cells. Consequently, msiCAT-tailing can foster cell survival and migration, whereas blocking msiCAT-tailing via genetic or pharmacological intervention can impede GBM cell overgrowth.

Natural populations are often spatially structured, meaning they exist as metapopulations composed of subpopulations connected by migration. Little is known about the impact of spatial structure, in particular the topology of connections among subpopulations, on adaptive evolution. Typically, spatial structure slows adaptation, although some models suggest topologies that concentrate dispersing individuals through a central hub can accelerate adaptation above that of a well-mixed system. We provide evidence to support this claim and show acceleration is accompanied by high rates of parallel evolution. Our results suggest metapopulation topology can be a potent force driving evolutionary dynamics and patterns of genomic repeatability in structured landscapes such as those involving the spread of pathogens or invasive species.

Humans routinely anticipate upcoming language, but whether such predictions come at a cognitive cost remains debated. In this study, we demonstrate the resource-dependent nature of predictive mechanisms in language comprehension across the lifespan: Experimentally limiting executive resources through a concurrent task reduces the effect of language predictability on reading time. Participants (N = 175, replication N = 96) read short articles presented word-by-word while completing a secondary font colour n-back task, thus varying cognitive demand. Language predictability was indexed by word surprisal as derived from a pre-trained large language model (GPT-2). Across two independent samples, our findings reveal that language predictions are not cost-free: They draw on executive control resources, and this dependency becomes more pronounced with age (18-85 years). These results help resolve the debate over cognitive demands in language comprehension and highlight prediction as a dynamic, resource-dependent process across the lifespan.

Tuberculosis (TB), caused by the bacterium Mycobacterium tuberculosis (Mtb), infects approximately one-fourth of the world's population. We reported an increased accumulation of mast cells (MCs) in the lungs of macaques with active pulmonary TB (PTB), compared with those with latent TB infection (LTBI). MCs respond in vitro to Mtb exposure via degranulation and by inducing proinflammatory cytokines. In the current study, we demonstrate an increased production of chymase by MCs in granulomas of humans and macaques with PTB. Single-cell (sc) RNA sequencing analysis revealed distinct MC transcriptional programs between LTBI and PTB, with PTB-associated MCs enriched in interferon gamma, oxidative phosphorylation, and MYC signaling. In a mouse model, MC deficiency led to improved control of Mtb infection that coincided with reduced accumulation of lung myeloid cells and diminished lung inflammation at chronic stages of infection. Airway transfer of MCs into wild-type Mtb-infected mice showed increased neutrophils, decreased recruited macrophages, and elevated Mtb dissemination to the spleen. Together, these findings highlight MCs as active drivers of TB pathogenesis and potential targets for host-directed therapies for TB.

The ability to learn and form memories is critical for animals to make choices that promote their survival. The biological processes underlying learning and memory are mediated by a variety of genes in the nervous system, acting at specific times during memory encoding, consolidation, and retrieval. Many studies have utilised candidate gene approaches or random mutagenesis screens in model animals to explore the key molecular drivers for learning and memory. We propose a complementary approach to identify this network of learning regulators: the proximity-labelling tool TurboID, which promiscuously biotinylates neighbouring proteins, to snapshot the proteomic profile of neurons during learning. To do this, we expressed the TurboID enzyme in the entire nervous system of Caenorhabditis elegans and exposed animals to biotin only during the training step of an appetitive gustatory learning paradigm. Our approach revealed hundreds of proteins specific to 'trained' worms, including components of molecular pathways previously implicated in memory in multiple species such as insulin signalling, G-protein-coupled receptor signalling, and MAP kinase signalling. Most (87-95%) of the proteins identified are neuronal, with relatively high representation for neuron classes involved in locomotion and learning. We validated several novel regulators of learning, including cholinergic receptors (ACC-1, ACC-3, LGC-46) and putative arginine kinase F46H5.3. These previously uncharacterised learning regulators all showed a clear impact on appetitive gustatory learning, with F46H5.3 showing an additional effect on aversive gustatory memory. Overall, we show that proximity labelling can be used in the brain of a small animal as a feasible and effective method to advance our knowledge on the biology of learning.