Miracle-dz/UniFAR-FTUs huggingface dataset:
Cancer-associated fibroblasts produce matrix-bound vesicles that influence endothelial cell function

Intercellular communication between different cell types in solid tumors contributes to tumor growth and metastatic dissemination. The secretome of cancer-associated fibroblasts (CAFs) plays major roles in these processes. Using human mammary CAFs, we showed that CAFs with a myofibroblast phenotype released extracellular vesicles that transferred proteins to endothelial cells (ECs) that affected their interaction with immune cells. Mass spectrometry–based proteomics identified proteins transferred from CAFs to ECs, which included plasma membrane receptors. Using THY1 as an example of a transferred plasma membrane–bound protein, we showed that CAF-derived proteins increased the adhesion of a monocyte cell line to ECs. CAFs produced high amounts of matrix-bound EVs, which were the primary vehicles of protein transfer. Hence, our work paves the way for future studies that investigate how CAF-derived matrix-bound EVs influence tumor pathology by regulating the function of neighboring cancer, stromal, and immune cells. Protein transfer through matrix-bound vesicles from CAFs enhances monocyte adhesion to endothelial cells. Editor’s summary Cancer-associated fibroblasts promote tumor growth, in part, by releasing extracellular vesicles, which can carry proteins to cells in the tumor microenvironment. Santi et al. investigated intercellular communication between endothelial cells in blood vessels and cancer-associated fibroblasts isolated from patients with breast cancer. Endothelial cells in vitro and in vivo took up proteins from extracellular vesicles, specifically matrix-bound vesicles, released by cancer-associated fibroblasts. Uptake of the membrane glycoprotein THY1 from cancer-associated fibroblasts increased the adhesion of monocytes to endothelial cells. Cancer-associated fibroblasts that released the most matrix-bound vesicles resembled myofibroblasts. Thus, identifying the proteins released by myofibroblast-like cancer-associated fibroblasts that alter endothelial cell function could yield potential targets for disrupting this intercellular communication. —Wei Wong
A truncation mutant of adenomatous polyposis coli (APC) impairs apical cell extrusion through elevated epithelial tissue tension

Tissue tension encompasses the mechanical forces exerted on solid tissues within animal bodies, originating from various sources such as cellular contractility, interactions with neighbouring cells and the extracellular matrix. Emerging evidence indicates that an imbalance in tissue tension can influence structural organisation, homeostasis and potentially contribute to disease. For instance, heightened tissue tension can impede apical cell extrusion, leading to the retention of apoptotic or transformed cells. In this study, we investigate the potential role of adenomatous polyposis coli (APC) in modulating tissue tension. Our findings reveal that expression of an APC truncation mutant elevates epithelial tension via the RhoA/ROCK pathway. This elevation induces morphological alterations and hampers apoptotic cell extrusion in cultured epithelial cells and organoids, both of which could be mitigated by pharmacologically restoring the tissue tension. This raises the possibility that APC mutations may exert pathogenetic effects by altering tissue mechanics.
Distinct regions within SAP25 recruit O-linked glycosylation, DNA demethylation, and ubiquitin ligase and hydrolase activities to the Sin3/HDAC complex

Epigenetic control of gene expression is crucial for maintaining gene regulation. Sin3 is an evolutionarily conserved repressor protein complex mainly associated with histone deacetylase (HDAC) activity. A large number of proteins are part of Sin3/HDAC complexes, and the function of most of these members remains poorly understood. SAP25, a previously identified Sin3A associated protein of 25 kDa, has been proposed to participate in regulating gene expression programs involved in the immune response but the exact mechanism of this regulation is unclear. SAP25 is not expressed in HEK293 cells, which hence serve as a natural knockout system to decipher the molecular functions uniquely carried out by this Sin3/HDAC subunit. Using molecular, proteomic, protein engineering, and interaction network approaches, we show that SAP25 interacts with distinct enzymatic and regulatory protein complexes in addition to Sin3/HDAC. While the O-GlcNAc transferase (OGT) and the TET1 /TET2/TET3 methylcytosine dioxygenases have been previously linked to Sin3/HDAC, in HEK293 cells, these interactions were only observed in the affinity purification in which an exogenously expressed SAP25 was the bait. Additional proteins uniquely recovered from the Halo-SAP25 pull-downs included the SCF E3 ubiquitin ligase complex SKP1/FBXO3/CUL1 and the ubiquitin carboxyl-terminal hydrolase 11 (USP11), which have not been previously associated with Sin3/HDAC. Finally, we use mutational analysis to demonstrate that distinct regions of SAP25 participate in its interaction with USP11, OGT/TETs, and SCF(FBXO3). ) These results suggest that SAP25 may function as an adaptor protein to coordinate the assembly of different enzymatic complexes to control Sin3/HDAC-mediated gene expression.
Towards Generative RNA Design with Tertiary Interactions

The design of RNAs that fulfill desired functions is one of the major challenges in computational biology. The function of an RNA molecule depends on its structure and a strong structure-to-function relationship is already achieved on the secondary structure level of RNA. Therefore, computational RNA design is often interpreted as the inversion of a folding algorithm: Given a target secondary structure, find an RNA sequence that folds into the desired structure. However, existing RNA design approaches cannot invert state-of-the-art folding algorithms because they can only predict a limited set of base interactions. In this work, we propose RNAinformer, a novel generative transformer based approach to the inverse RNA folding problem. Leveraging axial attention, we are able to process secondary structures represented as adjacency matrices, which allows us to invert state-of-the-art folding algorithms. Consequently, RNAinformer is the first model capable of designing RNAs from secondary structures without base pair restrictions. We demonstrate RNAinformer’s strong performance across different RNA design benchmarks and showcase its novelty by inverting a state-of-the-art deep learning based secondary structure prediction algorithm.
A low-footprint, fluorescence-based bacterial time-kill assay for estimating dose-dependent cell death dynamics

Dose-response curves that describe the relationship between antibiotic dose and growth rate in bacteria are commonly measured with optical density (OD) based assays. While being simple and high-throughput, any dose-dependent cell death dynamics are obscured, as OD assays in batch culture can only quantify a positive net change in cells. Time-kill experiments can be used to quantify cell death rates, but current techniques are extremely resource-intensive and may be biased by residual drug carried over into the quantification assay. Here, we report a novel, fluorescence-based time-kill assay leveraging resazurin as a viable cell count indicator. Our method improves upon previous techniques by greatly reducing the material cost and being robust to residual drug carry-over. We demonstrate our technique by quantifying a dose-response curve in Escherichia coli subject to cefotaxime, revealing dose-dependent death rates. We also show that our method is robust to extracellular debris and cell aggregation. Dose-response curves quantified with our method may provide a more accurate description of pathogen response to therapy, paving the way for more accurate integrated pharmacodynamic-pharmacokinetic studies.
Effect of pH on the thermostability and redox properties of cytochrome c552 from Wolinella succinogenes

Cytochrome c552 from Wolinella succinogenes is one of the few examples of a low reduction potential class I c-type cytochrome with a mixture of high/low spin state populations observed in its visible spectrum. Analysis of its structural model suggests that the heme is Met/His coordinated and highly solvent-exposed. This supports the hypothesis that it is the solvent accessibility of the propionate groups that controls the reduction potential of small c-type cytochromes. The visible spectra obtained at different pH values reveal the presence of a protonable group with a pKa of 7.3, which also influences the reduction potential of this small cytochrome c552 (Em0’ of 97 ± 5 mV, pH 7.0) and can be either an H2O/OH- group distantly coordinating the heme iron, or one of the propionate groups. The thermostability of cytochrome c552 has been studied by circular dichroism and differential scanning calorimetry, indicating a highly stable protein at pH 5-7 (90 °C to 77 °C).
metaRange: A framework to build mechanistic range models

Mechanistic or process-based models offer great insights into the range dynamics of species facing non-equilibrium conditions, such as climate and land-use changes or invasive species. Their consideration of underlying mechanisms relaxes the species-environment equilibrium assumed by correlative approaches, while also generating conservation-relevant indicators, such as range-wide abundance time-series and migration rates if demographically explicit. However, the computational complexity of mechanistic models limits their development and applicability to large spatiotemporal extents. We developed the R package ‘metaRange’ that is a modular framework to build population-based and metabolically constrained range models. It provides a function catalogue for users to calculate niche-based suitability, metabolic scaling, population dynamics, biotic interactions, and kernel-based dispersal, which may include directed movement. The framework’s modularity enables the user to combine, extend, or replace these functions, making it possible to customize the model to the ecology of the study system. The package supports an unlimited number of static or dynamic environmental factors as input, including climate and land use. As an example, we simulated 100 virtual species in Germany on a 1 km2 resolution over 110 years under realistic environmental fluctuations in three scenarios: without competition, with competition, and with competition and a generalist-specialist trade-off. The results are in accordance with theoretical expectations. Due to the population-level, the package can execute such extensive simulation experiments on regular enduser hardware in a short amount of time. We provide detailed technical documentation, both for the individual functions in the package as well as instructions on how to set up different types of model structures and experimental designs. The metaRange framework enables process-based simulations of range dynamic of multiple interacting species on a high resolution and low computational demand. We believe that it allows for theoretical insights and hypotheses testing about future range dynamics of real-world species, which may better support conservation policies targeting biodiversity loss mitigation.
A model of task-level human stepping regulation yields semistable walking

A simple lateral dynamic walker, with swing leg dynamics and three adjustable input parameters, is used to study how motor regulation affects frontal plane stepping. Motivated by experimental observations and phenomenological models, we imposed task-level multiobjective regulation targeting the walker’s optimal lateral foot placement at each step. The regulator prioritizes achieving step width and lateral body position goals to varying degrees by choosing a mixture parameter. Our model thus integrates a lateral mechanical template, which captures fundamental mechanics of frontal-plane walking, with a lateral motor regulation template, an empirically verified model of how humans manipulate lateral foot placements in a goal-directed manner. The model captures experimentally observed stepping fluctuation statistics and demonstrates how linear empirical models of stepping dynamics can emerge from first-principles nonlinear mechanics. We find that task-level regulation gives rise to a goal equivalent manifold in the system’s extended state space of mechanical states and inputs, a subset of which contains a continuum of period-1 gaits forming a semistable set: perturbations off of any of its gaits result in transients that return to the set, though typically to different gaits.
Modeling spatial contrast sensitivity in responses of primate retinal ganglion cells to natural movies

Retinal ganglion cells, the output neurons of the vertebrate retina, often display nonlinear summation of visual signals over their receptive fields. This creates sensitivity to spatial contrast, letting the cells respond to spatially structured visual stimuli, such as a contrast-reversing grating, even when no net change in overall illumination of the receptive field occurs. Yet, computational models of ganglion cell responses are often based on linear receptive fields. Nonlinear extensions, on the other hand, such as subunit models, which separate receptive fields into smaller, nonlinearly combined subfields, are often cumbersome to fit to experimental data, in particular when natural stimuli are considered. Previous work in the salamander retina has shown that sensitivity to spatial contrast in response to flashed images can be partly captured by a model that combines signals from the mean and variance of luminance signals inside the receptive field. Here, we extend this spatial contrast model for application to spatiotemporal stimulation and explore its performance on spiking responses that we recorded from retinas of marmosets under artificial and natural movies. We show how the model can be fitted to experimental data and that it outperforms common models with linear spatial integration, in particular for parasol ganglion cells. Finally, we use the model framework to infer the cells’ spatial scale of nonlinear spatial integration and contrast sensitivity. Our work shows that the spatial contrast model provides a simple approach to capturing aspects of nonlinear spatial integration with only few free parameters, which can be used to assess the cells’ functional properties under natural stimulation and which provides a simple-to-obtain benchmark for comparison with more detailed nonlinear encoding models.
Dynamic energy budget model for a bumble bee colony: Predicting the spatial distribution and dynamics of colonies across multiple seasons

Bumble bees are important pollinators of many crops around the world. In recent decades, agricultural intensification has resulted in significant declines in bumble bee populations and the pollination services they provide. Empirical studies have shown that this trend can be reversed, however, by enhancing the agricultural landscape with natural habitat, such as adding wildflower patches adjacent to crops. Despite the empirical evidence, the mechanisms behind these positive effects are not fully understood, and the specific characteristics of the enhanced natural habitat that would maximize benefits are unclear at this time. Theoretical studies, in the form of mathematical models, have proven useful in elucidating the underlying mechanisms and determining the optimal natural habitat configurations. Existing models, however, generally focus only on particular aspects of bumble bee behaviour; some models are accurate at describing population dynamics, while others are accurate at describing their spatial distribution. In this work, we build a unique model coupling population dynamics, using a whole-colony Dynamic Energy Budget (DEB) approach, to a spatial distribution model based on the maximum energy principle. This coupling gives valuable new insights into the effects of spatial arrangements on population dynamics, and vice-versa. With our model, we answer questions such as when, how much, or what type of wildflower patches should be planted to maximize crop pollination services and minimize bee decline. We find that planting wildflowers that bloom before and after crop bloom is crucial to achieve high pollination services and preserving wild pollinator populations. We also find that small quantities of natural habitat are needed when the crop is nutritionally rich, but higher quantities are most beneficial when the crop is nutritionally deficient.
La Crosse virus reassortants highlight genomic determinants of infection and pathogenesis

The genomic determinants that contribute to orthobunyavirus infection and pathogenesis are not well-defined. In this study, we harnessed the process of reassortment to understand which viral factors drive change in the replication and pathogenesis of La Crosse virus (LACV). We systematically reassorted the genomic segments of two genetically similar Lineage I LACV isolates into six unique reassortants. Despite the parental isolates having high levels of RNA and protein consensus, the reassortants demonstrate how minimal changes in RNA and protein structure can have significant changes in viral growth and reproduction in vitro in mammalian and insect models. We observed that swapping the S segment between isolates led to differences in replication and assembly resulting in one non-rescuable reassortant and one viable reassortant that exhibited an increase in viral growth dynamics. Switching the M segment led to changes in viral plaque phenotype and growth kinetics. L segment reassortants similarly differed in changes in viral growth dynamics. We further explored the M segment reassortants in a neonate mouse model and observed a role for the M segment in neuroinflammation and virulence. Through reassortment of the La Crosse virus genomic segments, we are able to further understand how genomic determinants of infection and pathogenesis operate in orthobunyaviruses. Future investigations will focus on identifying the specific molecular elements that govern the observed phenotypes in vitro and in vivo. Importance La Crosse virus is the leading cause of pediatric arboviral encephalitis in the United States, yet it is largely unknown how each of the three genomic segments contribute to pathogenesis and disease. Our study utilizes genomic reassortment between two similar Lineage I LACV isolates to understand genomic determinants for differences in infection and pathogenesis phenotypes in vitro and in vivo. By identifying roles for each segment in observed outcomes, we are able to plan further studies for molecular characterization of these phenotypes. Additionally, it is imperative to continue to characterize orthobunyavirus function since climate change will expand the range and prevalence of arthropod-borne diseases such as LACV in the United States.
Uncertainty-based causal inference modulates audiovisual temporal recalibration

Cross-modal temporal recalibration is crucial for maintaining coherent perception in a multimodal environment. The classic view suggests that cross-modal temporal recalibration aligns the perceived timing of sensory signals from different modalities, such as sound and light, to compensate for physical and neural latency differences. However, this view cannot fully explain the nonlinearity and asymmetry observed in audiovisual recalibration effects: the amount of re-calibration plateaus with increasing audiovisual asynchrony and varies depending on the leading modality of the asynchrony during exposure. To address these discrepancies, our study examines the mechanism of audiovisual temporal recalibration through the lens of causal inference, considering the brain’s capacity to determine whether multimodal signals come from a common source and should be integrated, or else kept separate. In a three-phase recalibration paradigm, we manipulated the adapter stimulus-onset asynchrony in the exposure phase across nine sessions, introducing asynchronies up to 0.7 s of either auditory or visual lead. Before and after the exposure phase in each session, we measured participants’ perception of audiovisual relative timing using a temporal-order-judgment task. We compared models that assumed observers re-calibrate to approach either the physical synchrony or the causal-inference-based percept, with uncertainties specific to each modality or comparable across them. Modeling results revealed that a causal-inference model incorporating modality-specific uncertainty captures both the nonlinearity and asymmetry of audiovisual temporal recalibration. Our results indicate that human observers employ causal-inference-based percepts to recalibrate cross-modal temporal perception.
Introducing CHiDO – a No Code Genomic Prediction Software implementation for the Characterization & Integration of Driven Omics

Climate change represents a significant challenge to global food security by altering environmental conditions critical to crop growth. Plant breeders can play a key role in mitigating these challenges by developing more resilient crop varieties; however, these efforts require significant investments in resources and time. In response, it is imperative to use current technologies that assimilate large biological and environmental datasets into predictive models to accelerate the research, development, and release of new improved varieties. Leveraging large and diverse data sets can improve the characterization of phenotypic responses due to environmental stimuli and genomic pulses. A better characterization of these signals holds the potential to enhance our ability to predict trait performance under changes in weather and/or soil conditions with high precision. This paper introduces CHiDO, an easy-to-use, no-code platform designed to integrate diverse omics datasets and effectively model their interactions. With its flexibility to integrate and process data sets, CHiDO’s intuitive interface allows users to explore historical data, formulate hypotheses, and optimize data collection strategies for future scenarios. The platform’s mission emphasizes global accessibility, democratizing statistical solutions for situations where professional ability in data processing and data analysis is not available. Core ideas The authors developed CHiDO, a platform for breeders to build predictive models integrating multi-omics data. CHiDO is a no-code tool that leverages the reaction norm model proposed by Jarquin et al. (2014). The platform aims to increase access to predictive analytics lowering relevant technical and financial barriers.
Microglia Depletion leads to Increased Susceptibility to Ocular Hypertension-Dependent Glaucoma

In recent years, microglia have been highlighted for playing integral roles in neurodegenerative diseases, like glaucoma. To better understand the role of microglia during chronic ocular hypertension, we depleted microglia from aged (9-12 months old) DBA/2J (D2) mice, which exhibit age-related increases in intraocular pressure, using a dietary CSF1R antagonist, PLX5622. Retinal ganglion cell (RGC) somas were counted, and optic nerve cross-sections stained and assessed for glaucomatous damage. Sustained administration of dietary PLX5622 significantly reduced the numbers of retinal microglia. Dietary PLX5622 did not lead to changes in intraocular pressure in D2 or normotensive DBA/2J-Gpnmb+ (D2-Gpnmb+) control mice. While PLX5622-treated D2-Gpnmb+ did not develop optic nerve damage, PLX5622-treated D2 mice showed a significant increase in moderate-to-severe optic nerve damage compared to D2 mice fed a control diet. In conclusion, global reduction of microglia exacerbated glaucomatous neurodegeneration in D2 mice suggesting microglia play an overall beneficial role in protecting from ocular hypertension associated RGC loss.