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Alamandine (ALA) exerts protective effects similar to angiotensin (Ang) (1-7) through Mas-related G protein-coupled receptor type D receptor (MrgDR) activation, distinct from Mas receptor (MasR). ALA induces anti-inflammatory effects in mice but its impact in human macrophages remains unclear. We aimed to investigate the anti-inflammatory effects of ALA in human macrophages. Interleukin (IL)-6 and IL-1ß were measured by ELISA in human THP-1 macrophages and human monocyte-derived macrophages exposed to lipopolysaccharide (LPS). Consequences of MasR-MrgDR heteromerization were investigated in transfected HEK293T cells. ALA decreased IL-6 and IL-1ß secretion in LPS-activated THP-1 macrophages. The ALA-induced decrease in IL-6 but not in IL-1ß was prevented by MasR blockade and MasR downregulation, suggesting MasR-MrgDR interaction. In human monocyte-derived M1 macrophages, ALA decreased IL-1ß secretion independently of MasR. MasR-MrgDR interaction was confirmed in THP-1 macrophages, human monocyte-derived macrophages, and transfected HEK293T cells. MasR and MrgDR formed a constitutive heteromer that was not influenced by ALA. ALA promoted Akt and ERK1/2 activation only in cells expressing MasR-MrgDR heteromers, and this effect was prevented by MasR blockade. While Ang-(1-7) reduced cellular proliferation in MasR -but not MrgDR- expressing cells, ALA antiproliferative effect was elicited in cells expressing MasR-MrgDR heteromers. ALA also induced an antiproliferative response in THP-1 cells and this effect was abolished by MasR blockade, reinforcing MasR-MrgDR interaction. MasR-MrgDR heteromerization is crucial for ALA-induced anti-inflammatory and antiproliferative responses in human macrophages. This study broaden our knowledge of the protective axis of the RAS, thus enabling novel therapeutic approaches in inflammatory-associated diseases.

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MOTIVATION: Chemical reaction networks (CRNs) play a pivotal role in diverse fields such as systems biology, biochemistry, chemical engineering, and epidemiology. High-level definitions of CRNs enables to use various simulation approaches, including deterministic and stochastic methods, from the same model. However, existing Python tools for simulation of CRN typically wrap external C/C++ libraries for model definition, translation into equations and/or numerically solving them, limiting their extensibility and integration with the broader Python ecosystem. RESULTS: In response, we developed Poincaré and SimBio, two novel Python packages for simulation of dynamical systems and CRNs. Poincaré serves as a foundation for dynamical systems modeling, while SimBio extends this functionality to CRNs, including support for the Systems Biology Markup Language (SBML). Poincaré and SimBio are developed as pure Python packages enabling users to easily extend their simulation capabilities by writing new or leveraging other Python packages. Moreover, this does not compromise the performance, as code can be just-in-time compiled with Numba. Our benchmark tests using curated models from the BioModels repository demonstrate that these tools may provide a potentially superior performance advantage compared to other existing tools. In addition, to ensure a user-friendly experience, our packages use standard typed modern Python syntax that provides a seamless integration with integrated development environments. Our Python-centric approach significantly enhances code analysis, error detection, and refactoring capabilities, positioning Poincaré and SimBio as valuable tools for the modeling community. AVAILABILITY AND IMPLEMENTATION: Poincaré and SimBio are released under the MIT license. Their source code is available on GitHub (https://github.com/maurosilber/poincare and https://github.com/hgrecco/simbio) and can be installed from PyPI or conda-forge.

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BACKGROUND: In tissues and organisms, the coordination of neighboring cells is essential to maintain their properties and functions. Therefore, knowing which cells are adjacent is crucial to understand biological processes that involve physical interactions among them, e.g. cell migration and proliferation. In addition, some signaling pathways, such as Notch or extrinsic apoptosis, are highly dependent on cell-cell communication. While this is straightforward to obtain from membrane images, nuclei labelling is much more ubiquitous for technical reasons. However, there are no automatic and robust methods to find neighboring cells based only on nuclear markers. RESULTS: In this work, we describe Nfinder, a method to assess the cell's local neighborhood from images with nuclei labeling. To achieve this goal, we approximate the cell-cell interaction graph by the Delaunay triangulation of nuclei centroids. Then, links are filtered by automatic thresholding in cell-cell distance (pairwise interaction) and the maximum angle that a pair of cells subtends with shared neighbors (non-pairwise interaction). We systematically characterized the detection performance by applying Nfinder to publicly available datasets from Drosophila melanogaster, Tribolium castaneum, Arabidopsis thaliana and C. elegans. In each case, the result of the algorithm was compared to a cell neighbor graph generated by manually annotating the original dataset. On average, our method detected 95% of true neighbors, with only 6% of false discoveries. Remarkably, our findings indicate that taking into account non-pairwise interactions might increase the Positive Predictive Value up to + 11.5%. CONCLUSION: Nfinder is the first robust and automatic method for estimating neighboring cells in 2D and 3D based only on nuclear markers and without any free parameters. Using this tool, we found that taking non-pairwise interactions into account improves the detection performance significantly. We believe that using our method might improve the effectiveness of other workflows to study cell-cell interactions from microscopy images. Finally, we also provide a reference implementation in Python and an easy-to-use napari plugin.

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Smaug is a conserved translational regulator that binds numerous mRNAs, including nuclear transcripts that encode mitochondrial enzymes. Smaug orthologs form cytosolic membrane-less organelles (MLOs) in several organisms and cell types. We have performed single-molecule fluorescence in situ hybridization (FISH) assays that revealed that SDHB and UQCRC1 mRNAs associate with Smaug1 bodies in U2OS cells. Loss of function of Smaug1 and Smaug2 (also known as SAMD4A and SAMD4B, respectively) affected both mitochondrial respiration and morphology of the mitochondrial network. Phenotype rescue by Smaug1 transfection depends on the presence of its RNA-binding domain. Moreover, we identified specific Smaug1 domains involved in MLO formation, and found that impaired Smaug1 MLO condensation correlates with mitochondrial defects. Mitochondrial complex I inhibition upon exposure to rotenone, but not strong mitochondrial uncoupling upon exposure to CCCP, rapidly induced the dissolution of Smaug1 MLOs. Metformin and rapamycin elicited similar effects, which were blocked by pharmacological inhibition of AMP-activated protein kinase (AMPK). Finally, we found that Smaug1 MLO dissolution weakens the interaction with target mRNAs, thus enabling their release. We propose that mitochondrial respiration and the AMPK-mTOR balance controls the condensation and dissolution of Smaug1 MLOs, thus regulating nuclear mRNAs that encode key mitochondrial proteins. This article has an associated First Person interview with the first authors of the paper.

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In this work we use lanthanide based NaYF4:Er3+, Yb3+upconversion nanoparticles (UCNP) to detect ppb-level sensitibity of a xanthene dye, Rhodamine B (RB) dye, under NIR excitation. A static energy transfer was observed between the luminescent UCNP energy donors and RB acceptor in aqueous solution for three different sizes of UCNP. No specific covalent functionalization of the UCNPs was performed providing a direct method of detection, particularly promising in natural systems where the interfering fluorescence background is a detrimental limitation to the performance of the detection method. This procedure is a first approach to be applied in estuarine and coastal zone where the high content of suspended particulate matter prevents the detection of tracers.

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Understanding signal propagation across biological networks requires to simultaneously monitor the dynamics of several nodes to uncover correlations masked by inherent intercellular variability. To monitor the enzymatic activity of more than two components over short time scales has proven challenging. Exploiting the narrow spectral width of homo-FRET-based biosensors, up to three activities can be imaged through fluorescence polarization anisotropy microscopy. We introduce Caspase Activity Sensor by Polarization Anisotropy Multiplexing (CASPAM) a single-plasmid triple-modality reporter of key nodes of the apoptotic network. Apoptosis provides an ideal molecular framework to study interactions between its three composing pathways (intrinsic, extrinsic, and effector). We characterized the biosensor performance and demonstrated the advantages that equimolar expression has in both simplifying experimental procedure and reducing observable variation, thus enabling robust data-driven modeling. Tools like CASPAM become essential to analyze molecular pathways where multiple nodes need to be simultaneously monitored.

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Gastrulation is a key event in animal embryogenesis during which germ layer precursors are rearranged and the embryonic axes are established. Cell polarization is essential during gastrulation, driving asymmetric cell division, cell movements, and cell shape changes. The furry (fry) gene encodes an evolutionarily conserved protein with a wide variety of cellular functions, including cell polarization and morphogenesis in invertebrates. However, little is known about its function in vertebrate development. Here, we show that in Xenopus, Fry plays a role in morphogenetic processes during gastrulation, in addition to its previously described function in the regulation of dorsal mesoderm gene expression. Using morpholino knock-down, we demonstrate a distinct role for Fry in blastopore closure and dorsal axis elongation. Loss of Fry function drastically affects the movement and morphological polarization of cells during gastrulation and disrupts dorsal mesoderm convergent extension, responsible for head-to-tail elongation. Finally, we evaluate a functional interaction between Fry and NDR1 kinase, providing evidence of an evolutionarily conserved complex required for morphogenesis.

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Apoptosis is a mechanism of programmed cell death in which cells engage in a controlled demolition and prepare to be digested without damaging their environment. In normal conditions, apoptosis is repressed until it is irreversibly induced by an appropriate signal. In adult organisms, apoptosis is a natural way to dispose of damaged cells and its disruption or excess is associated with cancer and autoimmune diseases. Apoptosis is regulated by a complex signaling network controlled by caspases, specialized enzymes that digest essential cellular components and promote the degradation of genomic DNA. In this work, we propose an effective description of the signaling network focused on caspase-3 as a readout of cell fate. We integrate intermediate network interactions into a nonlinear feedback function acting on caspase-3 and introduce the effect of pro-apoptotic stimuli and regulatory elements as a saturating activation function. We show that activation dynamics in the theory is similar to previously reported experimental results. We compute bifurcation diagrams and obtain cell fate maps describing how stimulus intensity and feedback strength affect cell survival and death fates. These fates overlap within a bistable region that depends on total caspase concentration, regulatory elements, and feedback nonlinearity. We study a strongly nonlinear regime to obtain analytical expressions for bifurcation curves and fate map boundaries. For a broad range of parameters, strong stimuli can induce an irreversible switch to the death fate. We use the theory to explore dynamical stimulation conditions and determine how cell fate depends on stimulation temporal patterns. This analysis predicts a critical relation between transient stimuli intensity and duration to trigger irreversible apoptosis. We derive an analytical expression for this critical relation, valid for short stimuli. Our description provides distinct predictions and offers a framework to study how this signaling network processes different stimuli to make a cell fate decision.

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Biological systems are spatially organized. This microscopic heterogeneity has been shown to produce emergent complex behaviors such as bistability. Even though the connection between spatiality and dynamic response is essential to understand biological output, its robustness and extent has not been sufficiently explored. This work focuses on a previously described system which is composed of two monostable modules acting on different cellular compartments and sharing species through linear shuttling reactions. One of the two main purposes of this paper is to quantify the frequency of occurrence of bistability throughout the parameter space and to identify which parameters and in which value ranges control the emergence and the properties of bistability. We found that a very small fraction of the sampled parameter space produced a bistable response. Most importantly, shuttling parameters were among the most influential ones to control this property. The other goal of this paper is to simplify the same system as much as possible without losing compartment-induced bistability. This procedure provided a simplified model that still connects two monostable systems by a reduced set of linear shuttling reactions that circulates all the species around the two compartments. Bistable systems are one of the main building blocks of more complex behaviors such as oscillations, memory, and digitalization. Therefore, we expect that the proposed minimal system provides insight into how these behaviors can arise from compartmentalization.

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Cell migration has been a subject of study in a broad variety of biological systems, from morphogenetic events during development to cancer progression. In this work, we describe single-cell movement in a modular framework from which we simulate the collective behavior of glioblastoma cells, the most prevalent and malignant primary brain tumor. We used the U87 cell line, which can be grown as a monolayer or spatially closely packed and organized in 3D structures called spheroids. Our integrative model considers the most relevant mechanisms involved in cell migration: chemotaxis of attractant factor, mechanical interactions and random movement. The effect of each mechanism is integrated into the overall probability of the cells to move in a particular direction, in an automaton-like approach. Our simulations fit and reproduced the emergent behavior of the spheroids in a set of migration assays where single-cell trajectories were tracked. We also predicted the effect of migration inhibition on the colonies from simple experimental characterization of single treated cell tracks. The development of tools that allow complementing molecular knowledge in migratory cell behavior is relevant for understanding essential cellular processes, both physiological (such as organ formation, tissue regeneration among others) and pathological perspectives. Overall, this is a versatile tool that has been proven to predict individual and collective behavior in U87 cells, but that can be applied to a broad variety of scenarios.

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In order to overcome intercellular variability and thereby effectively assess signal propagation in biological networks it is imperative to simultaneously quantify multiple biological observables in single living cells. While fluorescent biosensors have been the tool of choice to monitor the dynamics of protein interaction and enzymatic activity, co-measuring more than two of them has proven challenging. In this work, we designed three spectrally separated anisotropy-based Förster Resonant Energy Transfer (FRET) biosensors to overcome this difficulty. We demonstrate this principle by monitoring the activation of extrinsic, intrinsic and effector caspases upon apoptotic stimulus. Together with modelling and simulations we show that time of maximum activity for each caspase can be derived from the anisotropy of the corresponding biosensor. Such measurements correlate relative activation times and refine existing models of biological signalling networks, providing valuable insight into signal propagation.

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Förster resonant energy transfer measured by fluorescence lifetime imaging microscopy (FRET-FLIM) is the method of choice for monitoring the spatio-temporal dynamics of protein interactions in living cells. To obtain an accurate estimate of the molecular fraction of interacting proteins requires a large number of photons, which usually precludes the observation of a fast process, particularly with time correlated single photon counting (TCSPC) based FLIM. In this work, we propose a novel method named pawFLIM (phasor analysis via wavelets) that allows the denoising of FLIM datasets by adaptively and selectively adjusting the desired compromise between spatial and molecular resolution. The method operates by applying a weighted translational-invariant Haar-wavelet transform denoising algorithm to phasor images. This results in significantly less bias and mean square error than other existing methods. We also present a new lifetime estimator (named normal lifetime) with a smaller mean squared error and overall bias as compared to frequency domain phase and modulation lifetimes. Overall, we present an approach that will enable the observation of the dynamics of biological processes at the molecular level with better temporal and spatial resolution.

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Cellular functions emerge from the collective action of a large number of different proteins. Understanding how these protein networks operate requires monitoring their components in intact cells. Due to intercellular and intracellular molecular variability, it is important to monitor simultaneously multiple components at high spatiotemporal resolution. However, inherent trade-offs narrow the boundaries of achievable multiplexed imaging. Pushing these boundaries is essential for a better understanding of cellular processes. Here the motivations, challenges and approaches for multiplexed imaging of intracellular protein networks are discussed. © 2016 International Society for Advancement of Cytometry.

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We have developed a method for calibrating subnanometer movements of a piezoelectric actuator with picometer accuracy and for a wide range of frequencies. This range make this calibration useful for scanning probe microscopes, particularly for an apertureless scanning near-field optical microscope in which the tip is dithered to modulate the optical signal. The setup consists of a Michelson interferometer that has a mobile arm capable of moving more than one fringe. The piezoelectric actuator to be calibrated vibrates at the desired frequency in the other arm. Net displacement can be calculated by simultaneous measurement of an interferometric signal and its derivative. Hysteresis of the system can be also measured. It will be shown that the actuator response is linear only for the low-frequency region (in our case as much as approximately 10 kHz). Above that frequency range, higher harmonics appear and cannot be neglected to obtain real displacement. Finally, it will be shown that the use of higher harmonics in calibration or detection schemes (that rely on the linearity of the response) must be validated, and this technique has proved adequate for that purpose.