Biology subjects

Shin, S.

Publications and source records attributed to Shin, S..

108 records · Page 6Linked to original sources

bioRxiv2020

Dynamic modelling of the PI3K/mTOR signalling network uncovers biphasic dependence of mTORC1 activation on the mTORC2 subunit Sin1

The PI3K/mTOR signalling network critically regulates a broad array of important biological processes, including cell growth, metabolism and autophagy. Dysregulation of PI3K/mTOR signalling is associated with a variety of human diseases, including cancer and metabolic disorders. The mechanistic target of rapamycin (mTOR) is a kinase that functions as a core catalytic subunit in two physically and functionally distinct complexes termed mTOR complex 1 (mTORC1) and mTORC2, which also share other common components such as mLTS8 (also known as G{beta}L) and DEPTOR. Despite being the subject of intensive research, a full picture of how mTORC1/2 assembly and activity are coordinated, and how they are functionally connected remain to be fully characterised. This is due primarily to the complex network wiring, featuring a growing number of intricate feedback loops and post-translational modifications, which require quantitative systems-level approaches to decipher. Here, we integrate predictive computational modelling, in vitro experiments and -omics data analysis to elucidate the dynamic and emergent features of the PI3K/mTOR network behavior. We construct new mechanistic models of the network that encapsulate novel critical mechanistic details, including mTORC1/2 coordination by mLTS8 (de)ubiquitination, and Akt-to-mTORC2 positive feedback loop. Model simulations subsequently confirmed by experimental validation revealed a previously unknown biphasic, threshold-gated dependence of mTORC1 activity on the key mTORC2 subunit Sin1, which is robust against cell-to-cell variation in protein expression. Furthermore, our results support the essential role of mLST8 in both mTORC1 and 2 activity, and suggest mLST8 could serve as a viable therapeutic target in breast cancer. Overall, our integrated analyses provide fresh systems-level insights into the dynamic behavior of PI3K/mTOR signalling and shed new light on the complexity of this important network. AUTHOR SUMMARYSignalling networks are the key information-processing machineries that underpin the ability of living cells to respond proportionately to extra- (and intra-) cellular cues. The PI3K/mTOR signalling network is one of the most important signalling networks in human cells that regulates cellular response to hormones such as insulin, yet our understanding of the network behaviour remains far from complete. Here, we employed a highly integrative approach that combines predictive mathematical modelling, biological experimentation, and data analysis to gain novel systems-level insights into PI3K/mTOR signalling. We constructed new mathematical models of this complex network incorporating important regulatory mechanisms. In contrary to commonly held views that mTORC2 lies upstream and is a positive regulator of mTORC1, we found that their relationship is highly nonlinear and dose dependent. This finding has major implications for mTORC2-directed anti-cancer strategies as depending on the cellular contexts, blocking mTORC2 may reduce or even enhance mTORC1 activation, the latter could inadvertently blunt the effect of mTORC2 blockade. Furthermore, our results demonstrate that mLST8 is required for the assembly and activity of both mTOR complexes, and suggest mLST8 is a viable therapeutic target in breast cancer, notably breast cancer.

systems biology↗

bioRxiv2020

Are fleas highly modified Mecoptera? Phylogenomic resolution of Antliophora (Insecta: Holometabola)

Insect orders have been defined and stable for decades, with few notable exceptions (e.g., Blattodea and Psocoptera). One of the few remaining questions of order-level monophyly is that of Mecoptera in respect to the phylogenetic placement of Siphonaptera (fleas). We used a large set of transcriptomic nucleotide sequence data representing 56 species and more than 3,000 single-copy genes to resolve the evolutionary history of Antliophora, including fleas (Siphonaptera), scorpionflies and relatives (Mecoptera), and true flies (Diptera). We find that fleas and mecopterans together are the sister group of flies. However, our data and/or analyses are unable to distinguish whether fleas are sister to a monophyletic Mecoptera, or whether they arose from within extant mecopteran families, rendering Mecoptera paraphyletic. We did not detect parameter bias in our dataset after applying a broad range of detection methods. Counter to a previous hypothesis that placed fleas within Mecoptera as the sister group to wingless boreids (snow fleas), we found a potential sister group relationship between fleas and the enigmatic family Nannochoristidae. Although we lack conclusive evidence, it seems possible that fleas represent the most-species rich group of modern mecopterans and that their parasitic lifestyle and morphological adaptations have simply made them unrecognizable in respect to their order-level classification.

evolutionary biology↗

bioRxiv2020

Multiscale label-free volumetric holographic histopathology of thick-tissue slides with subcellular resolution

Histopathology relies upon the staining and sectioning of biological tissues, which can be laborious and may cause artefacts and distort tissues. Here, we demonstrate label-free volumetric imaging of thick-tissue slides, exploiting refractive index distributions as intrinsic imaging contrast. The present method systematically exploits label-free quantitative phase imaging techniques, volumetric reconstruction of intrinsic refractive index distributions in tissues, and numerical algorithms for the seamless stitching of multiple 3D tomograms and for reducing scattering-induced image distortion. We demonstrate demonstrated label-free volumetric imaging of thick tissues with the field of view of 2 mm x 1.75 mm x 0.2 mm with a spatial resolution of 170 nm x 170 nm x 1200 nm. The number of optical modes, calculated as the reconstructed volume divided by the size of the point spread function, was approximately 20 Giga voxels. We have also demonstrated that different tumour types, and a variety of precursor lesions and pathologies can be visualized with the present method. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/205633v1_ufig1.gif" ALT="Figure 1"> View larger version (98K): org.highwire.dtl.DTLVardef@dcf15corg.highwire.dtl.DTLVardef@16a05d3org.highwire.dtl.DTLVardef@1a48860org.highwire.dtl.DTLVardef@f57430_HPS_FORMAT_FIGEXP M_FIG C_FIG

pathology↗

bioRxiv2020

Human GBP1 promotes pathogen vacuole rupture and inflammasome activation during Legionella pneumophila infection

The inflammasome is an essential component of host defense against intracellular bacterial pathogens, such as Legionella pneumophila, the causative agent of the severe pneumonia Legionnaires disease. Inflammasome activation leads to recruitment and activation of caspases, which promote IL-1 family cytokine release and pyroptosis. In mice, interferon (IFN) signaling promotes inflammasome responses against L. pneumophila, in part through the functions of a family of IFN-inducible GTPases known as guanylate binding proteins (GBPs) (1). Within murine macrophages, IFN signaling promotes rupture of the L. pneumophila-containing vacuole (LCV), whereas GBPs are dispensable for vacuole rupture. Instead, GBPs facilitate the lysis of cytosol-exposed L. pneumophila. In contrast to mouse GBPs, the functions of human GBPs in inflammasome responses to L. pneumophila are poorly understood. Here, we show that IFN-{gamma} promotes caspase-1, caspase-4, and caspase-5 inflammasome activation during L. pneumophila infection and upregulates GBP expression in primary human macrophages. We find that human GBP1 is important for maximal IFN-{gamma}-driven inflammasome responses to L. pneumophila. Furthermore, IFN-{gamma} signaling promotes the rupture of LCVs. Intriguingly, in contrast to murine GBPs, human GBP1 targets the LCV in a T4SS-dependent manner and promotes vacuolar lysis, resulting in increased bacterial access to the host cell cytosol. Our findings show a key role for human GBP1 in targeting and disrupting pathogen-containing vacuoles and reveal mechanistic differences in how mouse and human GBPs promote inflammasome responses to L. pneumophila.

microbiology↗

bioRxiv2020

Conditional Pten knockout in parvalbumin- or somatostatin-positive neurons sufficiently leads to autism-related behavioral phenotypes

Disrupted GABAergic neurons have been extensively described in brain tissues from individuals with autism spectrum disorder (ASD) and animal models for ASD. However, the contribution of these aberrant inhibitory neurons to autism-related behavioral phenotypes is not well understood. We examined ASD-related behaviors in mice with conditional Pten knockout in parvalbumin (PV)-expressing or somatostatin (Sst)-expressing neurons, two common subtypes of GABAergic neurons. We found that mice with deletion of Pten in either PV-neurons or Sst-neurons displayed social deficits, repetitive behaviors and impaired motor coordination/learning. In addition, mice with one copy of Pten deletion in PV-neurons exhibited hyperlocomotion in novel open fields and home cages. We also examined anxiety behaviors and found that mice with Pten deletion in Sst-neurons displayed anxiety-like behaviors, while mice with Pten deletion in PV-neurons exhibited anxiolytic-like behaviors. These behavioral assessments demonstrate that Pten knockout in the subtype of inhibitory neurons sufficiently gives rise to ASD-core behaviors, providing evidence that both PV- and Sst-neurons may play a critical role in ASD symptoms.

neuroscience↗

bioRxiv2020

SRF is a non-histone methylation target of KDM2B and SET7 in the regulation of myogenesis

Demethylation of histone lysines, one of the most important modifications in transcriptional regulation, is associated with various physiological states. KDM2B is a histone H3K4, H3K36, and H3K79 demethylase associated with the repression of transcription. Here, we present a novel mechanism by which KDM2B demethylates serum response factor (SRF) K165 to negatively regulate muscle differentiation, which is counteracted by histone methyltransferase SET7. We show that KDM2B inhibited skeletal muscle differentiation by inhibiting the transcription of SRF-dependent genes. Both KDM2B and SET7 regulated the balance of SRF K165 methylation. SRF K165 methylation was required for the transcriptional activation of SRF and for the promoter occupancy of SRF-dependent genes. SET7 inhibitors blocked muscle cell differentiation. Taken together, these data indicate that SRF is a non-histone target of KDM2B and that the methylation balance of SRF maintained by KDM2B and SET7 plays an important role in muscle cell differentiation.

developmental biology↗

bioRxiv2020

Infected macrophages engage alveolar epithelium to metabolically reprogram myeloid cells and promote antibacterial inflammation

Alveolar macrophages are the primary immune cells that first detect lung infection. However, only one macrophage patrols every three alveoli. How this limited number of macrophages provides protection is unclear, as numerous pathogens block cell-intrinsic immune responses. The intracellular pathogen Legionella pneumophila inhibits host translation, thereby impairing the ability of infected macrophages to produce critical cytokines. Nevertheless, infected macrophages induce an IL-1-dependent inflammatory response by recruited myeloid cells that controls infection. Here, we show that collaboration with the alveolar epithelium is critical, in that IL-1 instructs the alveolar epithelium to produce GM-CSF. Intriguingly, GM-CSF drives maximal cytokine production in bystander myeloid cells by enhancing PRR-induced glycolysis. Our findings reveal that alveolar macrophages engage alveolar epithelial signals to metabolically reprogram myeloid cells and amplify antibacterial inflammation. One Sentence SummaryThe alveolar epithelium is a central signal relay between infected and bystander myeloid cells that orchestrates antibacterial defense.

immunology↗

bioRxiv2020

Unraveling the Mechanism of a LOV Domain Optogenetic Sensor: A Glutamine Lever Induces Unfolding of the Jα Helix

Light-activated protein domains provide a convenient, modular, and genetically encodable sensor for optogenetics and optobiology. Although these domains have now been deployed in numerous systems, the precise mechanism of photoactivation and the accompanying structural dynamics that modulate output domain activity remain to be fully elucidated. In the C-terminal light, oxygen, voltage (LOV) domain of plant phototropins (LOV2), blue light activation leads to formation of an adduct between a conserved Cys residue and the embedded FMN chromophore, rotation of a conserved Gln (Q513), and unfolding of a helix (J-helix) which is coupled to the output partner. In the present work, we focus on the allosteric pathways leading to J helix unfolding in Avena sativa LOV2 (AsLOV2) using an interdisciplinary approach involving molecular dynamics simulations extending to 7 s, time-resolved infrared spectroscopy, solution NMR spectroscopy, and in-cell optogenetic experiments. In the dark state, the side chain of N414 is hydrogen bonded to the backbone N-H of Q513. The simulations predict a lever-like motion of Q513 after Cys adduct formation resulting in loss of the interaction between the side chain of N414 and the backbone C=O of Q513, and formation of a transient hydrogen bond between the Q513 and N414 side chains. The central role of N414 in signal transduction was evaluated by site-directed mutagenesis supporting a direct link between J helix unfolding dynamics and the cellular function of the Zdk2-AsLOV2 optogenetic construct. Through this multifaceted approach, we show that Q513 and N414 are critical mediators of protein structural dynamics, linking the ultrafast (sub-ps) excitation of the FMN chromophore to the microsecond conformational changes that result in photoreceptor activation and biological function.

biophysics↗

bioRxiv2019

Measurements of 3-D morphology of individual red blood cells upon localized photothermal effects using gold nanorods

We investigated the in-situ photothermal response of human red blood cells (RBCs) by combining photothermal heat generation and 3D quantitative phase imaging techniques. Gold-nanorod-coated substrates were excited using near-infrared light to generate local heat to RBCs, and response was measured by imaging 3-D refractive index tomograms of cells under various near infrared (NIR) excitation conditions. On photothermal treatment, cell morphology changed from discoid to crescent shapes, cell volume and dry mass decreased, and hemoglobin concentration increased. We also investigated the irreversible deformation of RBCs when multiple intense excitation shocks are applied. These results provide a new understanding of thermodynamic aspects of cell biology and hematology. O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

biophysics↗

bioRxiv2019

Machine and deep learning single-cell segmentation and quantification of multi-dimensional tissue images

Increasingly, highly multiplexed in situ tissue imaging methods are used to profile protein expression at the single-cell level. However, a critical limitation is a lack of robust cell segmentation tools applicable for sections of tissues with a complex architecture and multiple cell types. Using human colorectal adenomas, we present a pipeline for cell segmentation and quantification that utilizes machine learning-based pixel classification to define cellular compartments, a novel method for extending incomplete cell membranes, quantification of antibody staining, and a deep learning-based cell shape descriptor. We envision that this method can be broadly applied to different imaging platforms and tissue types.

bioinformatics↗

bioRxiv2019

NSUN2 introduces 5-methylcytosines in mammalian mitochondrial tRNAs

Maintenance and expression of mitochondrial DNA is indispensable for proper function of the oxidative phosphorylation machinery. Post-transcriptional modification of mitochondrial RNA has emerged as one of the key regulatory steps of human mitochondrial gene expression. Mammalian NOP2/Sun RNA Methyltransferase Family Member 2 (NSUN2) has been characterised as an RNA methyltransferase that introduces 5-methylcytosine (m5C) in nuclear-encoded tRNAs, mRNAs, microRNA and noncoding RNAs. In these roles, NSUN2 has been associated with cell proliferation and differentiation. Pathogenic variants in NSUN2 have been linked with neurodevelopmental disorders. Here we employ spatially restricted proximity labelling and immunodetection to demonstrate that NSUN2 is imported into the matrix of mammalian mitochondria. Using three genetic models for NSUN2 inactivation - knockout mice, patient-derived fibroblasts and CRISPR/Cas9 knockout in human cells - we show that NSUN2 in necessary for the generation of m5C at positions 48, 49 and 50 of several mammalian mitochondrial tRNAs. Finally, we show that inactivation of NSUN2 does not have a profound effect on mitochondrial tRNA stability and oxidative phosphorylation in differentiated cells. We discuss the importance of the newly discovered function of NSUN2 in the context of human disease.

biochemistry↗

bioRxiv2018

Scalable Nonlinear Programming Framework for Parameter Estimation in Dynamic Biological System Models

We present a nonlinear programming (NLP) framework for the scalable solution of parameter estimation problems that arise in dynamic modeling of biological systems. Such problems are computationally challenging because they often involve highly nonlinear and stif differential equations as well as many experimental data sets and parameters. The proposed framework uses cutting-edge modeling and solution tools which are computationally efficient, robust, and easy-to-use. Specifically, our framework uses a time discretization approach that: i) avoids repetitive simulations of the dynamic model, ii) enables fully algebraic model implementations and computation of derivatives, and iii) enables the use of computationally efficient nonlinear interior point solvers that exploit sparse and structured linear algebra techniques. We demonstrate these capabilities by solving estimation problems for synthetic human gut microbiome community models. We show that an instance with 156 parameters, 144 differential equations, and 1,704 experimental data points can be solved in less than 3 minutes using our proposed framework (while an off-the-shelf simulation-based solution framework requires over 7 hours). We also create large instances to show that the proposed framework is scalable and can solve problems with up to 2,352 parameters, 2,304 differential equations, and 20,352 data points in less than 15 minutes. Competing methods reported in the computational biology literature cannot address problems of this level of complexity. The proposed framework is flexible, can be broadly applied to dynamic models of biological systems, and enables the implementation of sophisticated estimation techniques to quantify parameter uncertainty, to diagnose observability/uniqueness issues, to perform model selection, and to handle outliers.\n\nAuthor summaryConstructing and validating dynamic models of biological systems spanning biomolecular networks to ecological systems is a challenging problem. Here we present a scalable computational framework to rapidly infer parameters in complex dynamic models of biological systems from large-scale experimental data. The framework was applied to infer parameters of a synthetic microbial community model from large-scale time series data. We also demonstrate that this framework can be used to analyze parameter uncertainty, to diagnose whether the experimental data are sufficient to uniquely determine the parameters, to determine the model that best describes the data, and to infer parameters in the face of data outliers.

bioinformatics↗

bioRxiv2018

Implantable electrical stimulation bioreactor with liquid crystal polymer based electrodes for enhanced bone regeneration at mandibular large defects in rabbit

The osseous regeneration of large bone defects is still a major clinical challenge in maxillofacial and orthopedic surgery. Our previous studies demonstrated that electrical stimulation (ES) with biphasic current pulse showed proliferative effects on bone cells and enhanced secretion of bone-forming growth factors. This study presents an implantable electrical stimulation bioreactor with electrodes based on liquid crystal polymer (LCP), which has excellent bone-binding property. The bioreactor was implanted into a critical sized bone defect and subjected to ES for one week, where bone regeneration was evaluated four weeks after surgery using micro-CT. The effect of ES via bioreactor was compared with a sham control group and positive control group that received recombinant human bone morphogenetic protein (rhBMP)-2 (20 g). New bone volume per tissue volume (BV/TV) in the ES and rhBMP-2 groups increased to 171% (p < 0.001) and 210% (p < 0.001), respectively, compared to that in the sham control group. In the histological evaluation, there was no inflammation within bone defects and adjacent to LCP in all groups. This study showed that the ES bioreactor with LCP electrodes could enhance bone regeneration at large bone defects, where LCP can act as a mechanically resistant outer box without inflammation.

bioengineering↗

bioRxiv2018

Genomic signatures accompanying the dietary shift to phytophagy in polyphagous beetles

BackgroundThe diversity and evolutionary success of beetles (Coleoptera) are proposed to be related to the diversity of plants on which they feed. Indeed the largest beetle suborder, Polyphaga, mostly includes plant-eaters among its ~315,000 species. In particular, plants defend themselves with a diversity of specialized toxic chemicals. These may impose selective pressures that drive genomic diversification and speciation in phytophagous beetles. However, evidence of changes in beetle gene repertoires driven by such interactions remains largely anecdotal and without explicit hypothesis testing.\n\nResultsTo address this, we explored the genomic consequences of beetle-plant trophic interactions by performing comparative gene family analyses across 18 species representing the two most species-rich beetle suborders. We contrasted the gene contents of species from the mostly plant-eating suborder Polyphaga with those of the mainly predatory Adephaga. We found gene repertoire evolution to be more dynamic, with significantly more adaptive lineage-specific expansions, in the more speciose Polyphaga. Testing the specific hypothesis of adaptation to plant-feeding, we identified families of enzymes putatively involved in beetle-plant interactions that underwent adaptive expansions in Polyphaga. There was especially strong support for the selection hypothesis on large gene families for glutathione S-transferase and carboxylesterase detoxification enzymes.\n\nConclusionsOur explicit modeling of the evolution of gene repertoires across 18 species identifies adaptive lineage-specific gene family expansions that accompany the dietary shift towards plants in beetles. These genomic signatures support the popular hypothesis of a key role for interactions with plant chemical defenses, and for plant-feeding in general, in driving beetle diversification.

evolutionary biology↗

bioRxiv2018

Yeast Chd1p remodels nucleosomes with unique DNA unwrapping and translocation dynamics

Chromodomain-helicase-DNA-binding protein 1 (CHD1) remodels chromatin by translocating nucleosomes along DNA, but its mechanism remains poorly understood. Here, we employ a single-molecule fluorescence approach to characterize nucleosome remodeling by yeast CHD1 (Chd1p). We show that Chd1p translocates nucleosomes in steps of multiple base pairs per ATP. ATP binding to Chd1p induces a transient unwrapping of the exit-side DNA, and facilitates nucleosome translocation. ATP hydrolysis induces nucleosome translocation, which is followed by the rewrapping upon the release of the hydrolyzed nucleotide. Multiple Chd1ps binding to a single nucleosome sequentially moves a histone octamer with a preference to the center of DNA fragments, suggesting a new mechanism for regularly spaced nucleosome generation by Chd1p. Our results reveal the unique mechanism by which Chd1p remodels nucleosomes. Significance StatementThere are four major ATP-dependent chromatin remodeler families: SWI/SNF, ISWI, CHD, and INO80/SWR1. The remodeling mechanisms of SWI/SNF and ISWI chromatin remodelers have been elucidated through extensive single-molecule studies, but it remains poorly understood how CHD chromatin remodeler operate. We use single-molecule FRET techniques, and show that Yeast CHD1 uses unique mechanisms to remodel a nucleosome.

biophysics↗

bioRxiv2017

Label-free non-invasive quantitative measurement of lipid contents in individual microalgal cells using refractive index tomography

Microalgae are promising candidates for biofuel production due to their high lipid content. To facilitate utilization of the microalgae for biofuel, rapid quantification of the lipid contents in microalgae is necessary. However, conventional methods based on the chemical extraction of lipids require a time-consuming destructive extraction process. Here, we demonstrate label-free, non-invasive, rapid quantification of the lipid contents in individual micro-algal cells measuring the three-dimensional refractive index tomograms. We measure three-dimensional refractive index distributions within Nannochloropsis oculata cells and find that lipid droplets are identifiable in tomograms by their high refractive index. In addition, we alter N. oculata under nitrogen deficiency by measuring the volume, lipid weight, and dry cell weight of individual cells. Characterization of individual cells allows correlative analysis between the lipid content and size of individual cells.

bioengineering↗

bioRxiv2017

3D label-free imaging and analysis of Pinus pollen grains using optical diffraction tomography

O_LIThe structure of pollen grains is related to the reproductive function of the plants. Here, three-dimensional (3D) refractive index maps were obtained for individual conifer pollen grains using optical diffraction tomography (ODT).\nC_LIO_LIThe 3D morphological features of pollen grains from pine trees were investigated using measured refractive index maps, in which distinct substructures were clearly distinguished and analyzed.\nC_LIO_LIMorphological and physiochemical parameters of the pollen grains were quantified from the obtained refractive index (RI) maps and used to quantitatively study the interspecific differences of pollen grains from different strains.\nC_LIO_LIOur results demonstrate that ODT can assess the structure of pollen grains. This label-free and rapid 3D imaging approach may provide a new platform for understanding the physiology of pollen grains.\nC_LI

plant biology↗

bioRxiv2017

Visualization And Label-Free Quantification Of Microfluidic Mixing Using Quantitative Phase Imaging

Microfluidic mixing plays a key role in various fields, including biomedicine and chemical engineering. To date, although various approaches for imaging microfluidic mixing have been proposed, they provide only quantitative imaging capability and require for exogenous labeling agents. Quantitative phase imaging techniques, however, circumvent these problems and offer label-free quantitative information about concentration maps of microfluidic mixing. We present the quantitative phase imaging of microfluidic mixing in various types of PDMS microfluidic channels with different geometries; the feasibility of the present method was validated by comparing it with the results obtained by theoretical calculation based on Ficks law.

bioengineering↗