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Ahn, D.

Publications and source records attributed to Ahn, D..

9 recordsLinked to original sources

Molecular mechanism of naturally-encoded signaling-bias at the complement anaphylatoxin receptors

The conceptual framework of biased signaling has revolutionized our understanding of GPCR signaling and regulatory paradigms, and greatly impacted the efforts focused on the discovery of GPCR-targeted therapeutics. However, the mechanistic basis of biased signaling remains primarily defined based on synthetic ligands and receptor mutants with relatively limited progress in understanding naturally-encoded signaling-bias. Here, we present fundamental molecular and structural insights into naturally-encoded signaling-bias at the complement anaphylatoxin C5a receptors namely, C5aR1 and C5aR2. We first discover that C5a-d-Arg, the naturally-occurring version of C5a lacking the terminal arginine, exhibits robust G-protein signaling-bias at C5aR1, characterised by attenuated {beta}arr recruitment. This signaling-bias manifests in both cytokine release from primary human immune cells, and in vivo, during neutrophil mobilization. We combine the cryo-EM structures of C5a/C5a-d-Arg-C5aR1 complexes with MD simulation, site-directed mutagenesis, and cellular experiments to elucidate that the G-protein-bias exhibited by C5a-d-Arg results from a distinct orientation of TM7 and helix 8 in C5aR1 leading to inefficient GRK recruitment and receptor phosphorylation. Next, we determine the first cryo-EM structures of C5aR2, a naturally-encoded {beta}-arrestin-biased receptor, in an apo state, complexed with the natural agonists C5a and C5a-d-Arg, and three peptide agonists including a first-in-class, newly discovered C5aR2-selective agonist, R8Y. These structural snapshots reveal key differences between the binding of C5a and C5a- d-Arg to C5aR1 and C5aR2, and provide a molecular basis of functional specialization at these two receptors. Moreover, the structural insights also allow us to decipher the molecular basis of naturally-encoded signaling-bias at C5aR2 originating from a shallower cytoplasmic interface with hydrophobic interior pocket that is not permissive to efficient G-protein-coupling and activation. Finally, we also engineer and characterize loss-of-function and gain-of-function variants of C5aR1 and C5aR2, which in turn corroborate and validate the structural observations presented here. Collectively, our findings offer crucial insights into previously lacking molecular mechanisms of the naturally-encoded signaling-bias at GPCRs, which have broad implications not only for the general framework of biased-signaling, but also for novel therapeutic design.

biochemistry↗

Prediction of zoonotic virus-host transmissibility using comparative airway organoids

AbstractThe emergence of new pandemic zoonotic diseases is accelerating. However, current approaches to control after outbreaks often allow the epidemic or pandemic spread of new zoonotic diseases, exemplified by the case of COVID-19. Prediction of zoonotic transmissibility will help minimize the outbreaks and socioeconomic damage. Here, we established highly efficient comparative airway organoids with minimal components from a panel of mammalian species for long-term culture and passaging and validated their utility to predict the transmissibility of zoonotic pathogens. Airway organoids from each species recapitulated the airway histology and contained the major cell types in the airway. They recapitulated the known susceptibility of their host species and tissues to diverse viruses. Transcriptomic analyses revealed that organoids from susceptible species induced genes of anti-viral immune responses only in common upon exposure to the same virus, although each species organoids displayed differential gene expression profiles. Also, organoids of the same species displayed differential transcriptomic responses against different viruses but induced anti-viral immune genes only in common. Our work provides a roadmap for comprehensive species- and tissue-level organoid panels for quick and reproducible uncharacterized pathogen surveillance to predict and prevent the next pandemic.

developmental biology↗

Lactoferrin-Derived Peptide Chimera Induces Caspase-independent Cell Death in Multiple Myeloma

Lactoferrin-derived peptide chimera is a synthetic peptide that mimics the functional unit of lactoferrin with antibacterial activity. Antimicrobial peptides are promising candidates for cancer treatment. Although LF is known to have anticancer effects, to the best of our knowledge, its effects on multiple myeloma have not yet been studied. In this study, we explored the potential of lactoferrin-derived chimera for the treatment of multiple myeloma, a malignant clonal plasma cell disease of the bone marrow. Lactoferrin-derived chimera effectively inhibited MM1S, MM1R, and RPMI8226 multiple myeloma cell growth and induced the early and late phases of apoptosis, but not in normal peripheral blood mononuclear cells. Furthermore, lactoferrin-derived chimera modulates the relative expression of genes involved in survival, apoptosis, and mitochondrial dysfunction at the transcriptional level. Mitochondrial analysis revealed that lactoferrin-derived chimera triggered oxidative stress in multiple myeloma cells, leading to the generation of reactive oxygen species and a decline in mitochondrial membrane potential, resulting in mitochondrial dysfunction. Although lactoferrin-derived chimera did not cause caspase-dependent cell death, it induced nuclear translocation of apoptosis-inducing factor and endonuclease G, indicating the initiation of caspase-independent apoptosis. Overall, our data suggest that lactoferrin-derived chimera induces caspase-independent programmed cell death in multiple myeloma cell lines by increasing the nuclear translocation of apoptosis-inducing factor/endonuclease G. Therefore, lactoferrin-derived chimera has potential in multiple myeloma cancer therapies.

cancer biology↗

Peptide inhibitors targeting FOXO4-p53 interactions and inducing senescent cancer cell-specific apoptosis

Cellular senescence, marked by irreversible cell cycle arrest and the secretion of proinflammatory factors, contributes to aging and cancer recurrence. Chemotherapy can also induce senescence; senescent cells often resist apoptosis and promote tumor recurrence. The interaction between FOXO4 and p53 sustains cell survival. Herein, we used biophysical techniques and conducted cellular experiments to develop a peptide inhibitor targeting this interaction to eliminate senescent cancer cells. We identified key regions in the p53 transactivation domain (TAD) involved in FOXO4 binding and designed an optimized peptide inhibitor (CPP-CAND) with improved cell permeability. CPP-CAND showed high selectivity and potency in inducing apoptosis in senescent cells by disrupting FOXO4-p53 foci and activating caspase pathways. It is effective against senescent cancer cells induced by doxorubicin and cisplatin, highlighting its potential as a senolytic drug. Thus, CPP-CAND is a promising therapeutic candidate with improved selectivity, efficacy, and cost-effectiveness.

biochemistry↗

Gαs slow conformational transition upon GTP binding and a novel Gαs regulator

G proteins are major signaling partners for G protein-coupled receptors (GPCRs). Although stepwise structural changes during GPCR-G protein complex formation and guanosine diphosphate (GDP) release have been reported, no information is available with regard to guanosine triphosphate (GTP) binding. Here, we used a novel Bayesian integrative modeling framework that combines data from hydrogen-deuterium exchange mass spectrometry, tryptophan-induced fluorescence quenching, and metadynamics simulations to derive a kinetic model and atomic-level characterization of stepwise conformational changes incurred by the {beta}2-adrenergic receptor ({beta}2AR)-Gs complex after GDP release and GTP binding. Our data suggest rapid GTP binding and GTP-induced dissociation of Gs from {beta}2AR and G{beta}{gamma}, as opposed to a slow closing of the Gs -helical domain (AHD). Yeast-two-hybrid screening using Gs AHD as bait identified melanoma-associated antigen D2 (MAGE D2) as a novel AHD-binding protein, which was also shown to accelerate the GTP-induced closing of the Gs AHD.

molecular biology↗

Biophysical investigation of the dual binding surfaces of human transcription factors FOXO4 and p53

Cellular senescence is protective against external oncogenic stress, but its accumulation causes aging-related diseases. Forkhead box O4 (FOXO4) and p53 are human transcription factors known to promote senescence by interacting each other and activating p21 transcription. Inhibition of the interaction is a strategy for inducing apoptosis of senescent cells, but the binding surfaces that mediate the FOXO4-p53 interaction remain elusive. Here, we investigated two binding sites involved in the interaction between FOXO4 and p53 by NMR spectroscopy. NMR chemical shift perturbation analysis showed that the binding between FOXO4s forkhead domain (FHD) and p53s transactivation domain (TAD), and between FOXO4s C-terminal transactivation domain (CR3) and p53s DNA binding domain (DBD), mediate the FOXO4-p53 interaction. Isothermal titration calorimetry data showed that both interactions have micromolar Kd values, and FOXO4 FHD-p53 TAD interaction has a higher binding affinity. Also, we showed that the FOXO4 CR3-binding surface of FOXO4 FHD interacts with p53 TAD2, and FOXO4 CR3 interacts with the DNA/p53 TAD-binding surface of p53 DBD, suggesting a network of potentially competitive and/or coordinated interactions. Based on the results, we propose that the dual interaction contributes to two TFs proper location on the p21 promoter site and consequently promotes p21 transcription and cell senescence. This work provides structural information at the molecular level that is key to understanding the interplay of two proteins responsible for cellular senescence. Conflicts of interestNone

biochemistry↗

Rapid and label-free identification of individual bacterial pathogens exploiting three-dimensional quantitative phase imaging and deep learning

The healthcare industry is in dire need for rapid microbial identification techniques. Microbial infection is a major healthcare issue with significant prevalence and mortality, which can be treated effectively during the early stages using appropriate antibiotics. However, determining the appropriate antibiotics for the treatment of the early stages of infection remains a challenge, mainly due to the lack of rapid microbial identification techniques. Conventional culture-based identification and matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy are the gold standard methods, but the sample amplification process is extremely time-consuming. Here, we propose an identification framework that can be used to measure minute quantities of microbes by incorporating artificial neural networks with three-dimensional quantitative phase imaging. We aimed to accurately identify the species of bacterial bloodstream infection pathogens based on a single colony-forming unit of the bacteria. The successful distinction between a total of 19 species, with the accuracy of 99.9% when ten bacteria were measured, suggests that our framework can serve as an effective advisory tool for clinicians during the initial antibiotic prescription. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/596486v2_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@786668org.highwire.dtl.DTLVardef@8b4eb4org.highwire.dtl.DTLVardef@1dc2452org.highwire.dtl.DTLVardef@1d4888c_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

Deep-learning-based label-free segmentation of cell nuclei in time-lapse refractive index tomograms

In order to identify cell nuclei, fluorescent proteins or staining agents has been widely used. However, use of exogenous agents inevitably prevents from long-term imaging of live cells and rapid analysis, and even interferes with intrinsic physiological conditions. In this work, we proposed a method of label-free segmentation of cell nuclei in optical diffraction tomography images by exploiting a deep learning framework. The proposed method was applied for precise cell nucleus segmentation in two, three, and four-dimensional label-free imaging. A novel architecture with optimised training strategies was validated through cross-modality and cross-laboratory experiments. The proposed method would bring out broad and immediate biomedical applications with our framework publicly available.

biophysics↗

Pathway-specific asymmetries between ON and OFF visual signals

Visual processing is largely organized into ON and OFF pathways that signal stimulus increments and decrements, respectively. These pathways exhibit natural pairings based on morphological and physiological similarities, such as ON and OFF alpha ganglion cells in the mammalian retina. Several studies have noted asymmetries in the properties of ON and OFF pathways. For example, the spatial receptive fields (RFs) of OFF alpha cells are systematically smaller than ON alpha cells. Analysis of natural scenes suggests these asymmetries are optimal for visual encoding. To test the generality of ON-OFF asymmetries, we measured the spatiotemporal RF properties of multiple RGC types in rat retina. Through a quantitative and serial classification, we identified three functional pairs of ON and OFF RGCs. We analyzed the structure of their RFs and compared spatial integration, temporal integration, and gain across ON and OFF pairs. Similar to previous results from cat and primate, RGC types with larger spatial RFs exhibited briefer temporal integration and higher gain. However, each pair of ON and OFF RGC types exhibited distinct asymmetric relationships between receptive field properties, some of which were opposite to previous reports. These results reveal the functional organization of six RGC types in the rodent retina and indicate that ON-OFF asymmetries are pathway specific.

neuroscience↗