Communications Biology最新文献

The cuticle is a polymeric membrane covering all plant aerial organs of primary origin. It regulates water loss and defends against environmental stressors and pathogens. Despite its significance, understanding of the micro-mechanical properties of the cuticle (cuticular membrane; CM) remains limited. In this study, non-invasive Brillouin light scattering (BLS) spectroscopy was applied to probe the micro-mechanics of native CM, dewaxed CM (DCM), and isolated cutin matrix (CU) of mature apple fruit. The BLS signal arises from the photon interaction with thermally induced pressure waves and allows for imaging with mechanical contrast. The derived loss tangent showed significant differences with wax extraction from the CM and further with carbohydrate extraction from the DCM, consistent with tensile test results. Spatial heterogeneity between anticlinal and periclinal regions was observed by BLS microscopy of CM and DCM, but not in CU. The key conclusions are: (1) BLS is sensitive to micro-mechanical variations, particularly the strain-stiffening effect of the cutin framework, offering insights into the CM's micro-mechanical behavior and underlying chemical structures; (2) CM and DCM exhibit spatial micro-mechanical heterogeneity between periclinal and anticlinal regions.

Phosphodiesterase 4D interacting protein (PDE4DIP) is a Golgi/centrosome-associated protein that plays critical roles in the regulation of microtubule dynamics and maintenance of the Golgi structure. However, its biological role in human cancer remains largely unknown. In this study, we showed that PDE4DIP is overexpressed in human non-small cell lung cancer (NSCLC) tissues and that upregulated PDE4DIP expression is associated with poor prognosis in patients with lung cancer. We demonstrated that PDE4DIP knockdown inhibits NSCLC cell proliferation in vitro and tumorigenicity in vivo. We further demonstrated that PDE4DIP knockdown triggers apoptosis and cell cycle arrest in NSCLC cells by activating the Protein kinase A (PKA) /CREB signalling pathway. PDE4DIP coordinates with A-kinase anchoring proteins 9 (AKAP9) to enhance the Golgi localization and stability of PKA RIIα. Depletion of PDE4DIP mislocalizes PKA RIIα from the Golgi and leads to its degradation, thereby compromising its negative regulatory effect on PKA signalling. Overall, our findings provide novel insights into the roles of the PDE4DIP-AKAP9 complex in regulating PKA signalling and NSCLC growth and highlight PDE4DIP as a promising therapeutic target for NSCLC.

Peptide-based drugs often fail in clinical trials due to their toxicity or hemolytic activity against red blood cells (RBCs). Existing methods predict hemolytic peptides but not the concentration (HC₅₀) required to lyse 50% of RBCs. This study develops classification and regression models to identify and quantify hemolytic activity. These models train on 1926 peptides with experimentally determined HC₅₀ against mammalian RBCs. Analysis indicates that hydrophobic and positively charged residues were associated with higher hemolytic activity. Among classification models, including machine learning (ML), quantum ML, and protein language models, a hybrid model combining random forest (RF) and a motif-based approach achieves the highest area under the receiver operating characteristic curve (AUROC) of 0.921. Regression models achieve a Pearson correlation coefficient (R) of 0.739 and a coefficient of determination (R²) of 0.543. These models outperform existing methods and are implemented in HemoPI2, a web-based platform and standalone software for designing peptides with desired HC₅₀ values ( http://webs.iiitd.edu.in/raghava/hemopi2/ ).

The understanding of selective forces driving the compartmentalization of microbiota in plants remains limited. In this study, we performed a phenotypic characterization of bacterial endophytes isolated from the medicinal plant Origanum heracleoticum, together with the determination of the antibiotic resistance profiles and the antagonistic interactions of communities within and across different plant organs. Results revealed organ-related differences in the metabolic capabilities of bacteria, with those associated with stems displaying the highest metabolic activity for carbon sources. Contrarily, the patterns of antibiotic resistance appeared closely aligned with the taxonomical classification of the endophytes. The presence of antagonistic interactions, likely spurred by resource limitations, favor bacteria exhibiting greater metabolic plasticity. In conclusion, this research advances our comprehension of the intricate dynamics between plants and their associated microbiota, indicating that its composition is mainly influenced by forces contributing to the selection of distinct functions and phenotypic traits.

A cognitive map is an internal model of the world's causal structure, crucial for adaptive behaviors. The orbitofrontal cortex (OFC) is central node to decision-making and cognitive map representation. However, it remains unclear how the medial OFC (mOFC) and lateral OFC (lOFC) contribute to the formation of cognitive maps in humans. By performing a multi-step sequential task and multivariate analyses of functional magnetic resonance imaging (fMRI) data, we found that the mOFC and lOFC play complementary but dissociable roles in this process. Specifically, the mOFC represents all hidden task state components. The lOFC and dorsolateral prefrontal cortex (dlPFC) encode abstract rules governing structure knowledge across task states. Furthermore, the two orbitofrontal subregions are functionally connected to share state-hidden information for constructing a representation of the task structure. Collectively, these findings provide an account that can increase our understanding of how the brain constructs abstract cognitive maps in a task-relevant space.

Human induced pluripotent stem cell (iPSC)-derived lung organoids, engineered to carry targeted genes, offer a robust platform for investigating mechanistic insights in lung research. Although lentiviral vectors (LVVs) are highly effective for stable expression due to their integrative properties, achieving efficient transduction in human iPSC-derived lung organoids poses a significant technical challenge, likely due to the complex structure of these organoids. In this study, we optimized a method to enhance LVV transduction efficiency by physically disrupting the organoids to increase surface area, followed by spinoculation to apply shear force during cell dissociation. This approach, combined with the use of an optimized culture medium, significantly improved transduction efficiency. The success of this method was validated at both the gene and protein levels using single-cell RNA sequencing (scRNA-seq) and various cellular and molecular assays. Our optimized transduction protocol may provide a valuable tool for investigating specific cellular and molecular mechanisms in development and disease models using human iPSCs-derived lung organoids.

The selection of high-performing cell lines is crucial for biopharmaceutical production but is often time-consuming and labor-intensive. We investigated label-free multimodal nonlinear optical microscopy for non-perturbative profiling of biopharmaceutical cell lines based on their intrinsic molecular contrast. Employing simultaneous label-free autofluorescence multiharmonic (SLAM) microscopy with fluorescence lifetime imaging microscopy (FLIM), we characterized Chinese hamster ovary (CHO) cell lines at early passages (0-2). A machine learning (ML)-assisted analysis pipeline leveraged high-dimensional information to classify single cells into their respective lines. Remarkably, the monoclonal cell line classifiers achieved balanced accuracies exceeding 96.8% as early as passage 2. Correlation features and FLIM modality played pivotal roles in early classification. This integrated optical bioimaging and machine learning approach presents a promising solution to expedite cell line selection process while ensuring identification of high-performing biopharmaceutical cell lines. The techniques have potential for broader single-cell characterization applications in stem cell research, immunology, cancer biology and beyond.

Acute lung injury (ALI), a frequent and severe complication of sepsis, is associated with significant mortality rates. Previous studies indicated that GLS2 plays a key role in promoting ferroptosis. However, its underlying mechanisms remain unclear. Here we show, there were elevated ferroptosis and increased expression levels of protein arginine methyltransferase 1 (PRMT1), early growth response 1 (EGR1), and glutaminase 2 (GLS2) in both in vitro and in vivo ALI models. Additionally, EGR1 was found to induce the transcription of GLS2, thereby promoting ferroptosis. We also discovered that the protein level of EGR1 was increased through enhanced stability, facilitated by PRMT1-mediated arginine methylation, and reduced ubiquitination degradation regulated by neural precursor cell expressed developmentally down-regulated protein 4 like (NEDD4L). The in vivo results confirmed that the knockdown of PRMT1 suppressed ferroptosis via the EGR1/GLS2 axis. Our findings suggest that PRMT1-mediated stabilization of EGR1 promoted sepsis induced ALI via GLS2, highlighting the therapeutic potential of targeting PRMT1 or EGR1 in the treatment of sepsis-induced ALI.

The threat of climate change has renewed interest in the responses of communities and ecosystems to warming, with changes in size spectra expected to signify fundamental shifts in the structure and dynamics of these multispecies systems. While substantial empirical evidence has accumulated in recent years on such changes, we still lack general insights due to a limited coverage of warming scenarios that span spatial and temporal scales of relevance to natural systems. We addressed this gap by conducting an extensive freshwater mesocosm experiment across 36 large field mesocosms exposed to intergenerational warming treatments of up to +8 °C above ambient levels. We found a nonlinear decrease in the overall mean body size of zooplankton with warming, with a 57% reduction at +8 °C. This pattern was broadly consistent over two tested seasons and major taxonomic groups. We also detected some breakpoints in the community-level size-temperature relationship, indicating that the system's response shifts noticeably above a certain level of warming. These results underscore the need to capture intergenerational responses to large gradients in warming at appropriate scales in time and space in order to better understand the effects of warming on natural communities and ecosystems.

Midbrain dopamine cells encode differences in predictive and expected value to support learning through reward prediction error. Recent findings have questioned whether reward prediction error can fully account for dopamine function and suggest a more complex role for dopamine in encoding detailed features of the reward environment. In this series of studies, we describe a novel role for dopamine in devaluing sensory features of reward. Mesencephalic dopamine cells activated during a mediated devaluation phase were later chemogenetically reactivated. This retrieval of the devalued reward memory elicited a reduction in the hedonic evaluation of sucrose reward. Through optogenetic and chemogenetic manipulations, we confirm dopamine cells are both sufficient and necessary for mediated devaluation, and retrieval of these memories reflected dopamine release in the nucleus accumbens. Consistent with our computational modeling data, our findings indicate a critical role for dopamine in encoding predictive representations of the sensory features of reinforcement. Overall, we elucidate a novel role for dopamine function in mediated devaluation and illuminate a more elaborate framework through which dopamine encodes reinforcement signals.