Biology subjects

Chen, Y.-C.

Publications and source records attributed to Chen, Y.-C..

At least 91 records · Page 5Linked to original sources

bioRxiv2022

Quantum CART (qCART), a piggyBac-based system for development and production of virus-free multiplex CAR-T cell therapy

Chimeric antigen receptor T (CAR-T) cell therapy has the potential to transform cancer treatment. However, CAR-T therapy application is currently limited to certain types of relapsed/refractory B cell lymphomas. To unlock the full potential of CAR-T therapy, technologic breakthroughs will be needed in multiple areas, including optimization of autologous CAR-T development, shortening the innovation cycle, and further manufacturing advancement of next-generation CAR-T therapies. Here, we established a simple and robust virus-free multiplex Quantum CART system that seamlessly and synergistically integrates four platforms: 1. GTailor for rapid identification of lead CAR construct design, 2. Quantum Nufect for effective but gentle electroporation-based gene delivery, 3. Quantum pBac, featuring a virus-free transposon-based vector with large payload capacity and integration profile similar to retrovirus, and 4. iCellar for robust and high-quality CAR+ T memory stem cell expansion. This robust, virus-free multiplex Quantum CART system is expected to unleash the full potential of CAR-T therapy for treating diseases.

cancer biology↗

bioRxiv2022

Manufacturing highly potent CD20/CD19-targeted iCasp9 regulatable CAR-T cells using the Quantum pBac-based CAR-T (qCART) system for clinical application

BackgroundCD19-targeted chimeric antigen receptor therapies (CAR19) have driven a paradigm shift in the treatment of relapsed/refractory B-cell malignancies. However, >50% of CAR19-treated patients experienced progressive disease mainly due to antigen escape and low persistence. Clinical prognosis is heavily influenced by CAR-T cell function and systemic cytokine toxicities. Furthermore, it remains a challenge to efficiently, cost-effectively, and consistently manufacture clinically relevant number of virally engineered CAR-T cells. MethodsUsing a highly efficient piggyBac transposon-based vector, Quantum pBac, we developed a virus-free cell engineering system, Quantum CART (qCART), for development and production of multiplex CAR-T therapies. ResultsHere, we demonstrated in vitro and in vivo that consistent, robust, and functional CD20/CD19 dual-targeted CAR-T stem cell memory (TSCM) cells can be efficiently manufactured using the qCART system for clinical application. qCART-manufactured CAR-T cells from cancer patients expanded efficiently, rapidly eradicated tumors, and can be safely controlled via an iCasp9 suicide gene-inducing drug. ConclusionsThe qCART system is an elegant system for the manufacturing of CAR-T products having all the desired CAR-T therapy attributes. We believe that the simplicity of manufacturing multiplex CAR-T cells using the qCART system will not only significantly enhance the accessibility of CAR-T therapy but also unlock the full potential of armored CAR-T therapy for the treatment of solid tumors in the future. What is already known on this topicDespite the considerable success which has been achieved with CD19-targeted chimeric antigen receptor therapies (CAR19), >50% of CAR19-treated patients still experienced progressive disease. Therefore, there is a need to further improve CAR19 therapies. Current CAR19 therapies commonly utilize virus-based cell engineering methods. CAR-T production using these methods face multiple hurdles, including difficulties to efficiently, cost-effectively, and consistently manufacture clinically relevant number of CAR-T cells. We have previously used a highly efficient piggyBac transposon-based vector, Quantum pBac, to establish Quantum CART (qCART) which is a virus-free cell engineering system for development and production of multiplex CAR-T therapies. What this study addsIn this report, we further demonstrate in vitro and in vivo that consistent, robust, and functional iCasp9-regulatable, CD20/CD19 dual-targeted CAR-T stem cell memory (TSCM) cells can be efficiently manufactured using the qCART system for clinical application. These cells possess all the desired attributes for ensuring therapeutic efficacy in CAR-T therapy, including high CAR-TSCM, balanced CD8/CD4 ratio, low exhaustion and senescence marker expressions, and high ex vivo and in vivo expansion capacity. Importantly, we show that qCART-manufactured CAR-T cells from hematological cancer patients expanded efficiently, effectively eradicated tumors, and can be safely controlled via an iCasp9 suicide gene-inducing drug. We believe that the simplicity of manufacturing multiplex CAR-T cells using the qCART system will not only significantly enhance the accessibility of CAR-T therapy but also unlock the full potential of armored CAR-T therapy for the treatment of solid tumors in the future. How this study might affect research, practice or policyOur findings demonstrate that qCART is a virus-free CAR-T engineering system for manufacturing CAR-TSCM cells from either healthy donors or hematological cancer patients, that possess all the desired attributes for a successful CAR-T therapy. These cells expanded efficiently, rapidly eradicated tumors, and can be safely controlled via activation of iCasp9. We expect that this simple yet robust system for manufacturing multiplex CAR-T cells will advance the CAR-T field.

cancer biology↗

bioRxiv2022

Functional brain region-specific neural spheroids for modeling neurological diseases and therapeutics screening

3D spheroids have emerged as powerful drug discovery tools given their high-throughput screening (HTS) compatibility. Here, we established a method for generating functional neural spheroids with differentiated human induced pluripotent stem cell (hiPSC)-derived neurons and astrocytes at cell type compositions mimicking specific regions of the human brain. Recordings of intracellular calcium oscillations were used as functional assays, and the utility of this spheroids system was shown through disease modelling, drug testing, and formation of assembloids to model neurocircuitry. We developed disease models for Alzheimers and Parkinsons Disease through incorporating genetically engineered cells into spheroids, and Opioid Use Disorder by chronically treating spheroids with DAMGO. We reversed baseline functional deficits in each disease model with clinically approved treatments and showed that assembloid activity can be chemogenetically manipulated. Here, we lay the groundwork for brain region-specific spheroids as a robust functional assay platform for HTS studies.

bioengineering↗

bioRxiv2022

Quantum pBac: An effective, high-capacity piggyBac-based gene integration vector system for unlocking gene therapy potential

Recent advances in gene therapy have brought novel treatment options for cancer. However, the full potential of this approach has yet to be unlocked due to the safety concerns and limited payload capacity of commonly utilized viral vectors. Virus-free DNA transposons, including piggyBac, have potential to obviate these shortcomings. In this study, we improved a previously developed modified piggyBac system with superior transposition efficiency. We demonstrated that the internal domain sequences (IDS) within the 3 terminal repeat domain of hyperactive piggyBac (hyPB) donor vector contain dominant enhancer elements. Plasmid-free donor vector devoid of IDS was used in conjunction with a helper plasmid expressing Quantum PBase v2 to generate an optimal piggyBac system, Quantum pBac (qPB), for use in T cells. Cells transfected with qPB expressing CD20/CD19 CAR outperformed those transfected with the same donor vector and plasmid expressing hyPB transposase in terms of CAR-T cell production. Importantly, qPB yielded mainly CD8+ CAR-TSCM cells, and the qPB- induced CAR-T cells effectively eliminated CD20/CD19-expressing tumor cells both in vitro and in vivo. Our findings confirm qPB as a promising virus-free vector system with a payload capacity to incorporate multiple genes. This system is highly efficient and potentially safe for mediating transgene integration.

cancer biology↗

bioRxiv2022

Detecting intragenic trans-splicing events with hybrid transcriptome sequencing in cancer cells

Trans-splicing can generate non-co-linear (NCL) transcripts that consist of exons in an order topologically inconsistent with the corresponding DNA template. Detecting trans-spliced RNAs (ts-RNAs) may be interfered by false positives from experimental artifacts, circular RNAs (circRNAs), and genetic rearrangements. Particularly, intragenic ts-RNAs, which are derived from separate precursor mRNA molecules of the same genes, are often mistaken for circRNAs through analyses of high-throughput transcriptome sequencing (RNA-seq) data. In addition, the biogenesis and function of ts-RNAs remain elusive. Here we developed a bioinformatics pipeline, NCLscan-hybrid, with the integration of long and short RNA-seq reads to minimize false positives and identify intragenic ts-RNAs. We utilized two features of long reads, out-of-circle and rolling circle, to distinguish intragenic ts-RNAs from circRNAs. We also designed multiple experimental validation steps to examine each type of false positives and successfully confirmed an intragenic ts-RNA (ts-ARFGEF1) in breast cancer cells. On the basis of ectopic expression and CRISPR-based endogenous genome modification experiments, we confirmed that ts-ARFGEF1 formation was significantly dependent on the reverse complementary sequences in the flanking introns of the NCL junction. Subsequent in vitro and in vivo experiments demonstrated that ts-ARFGEF1 silencing can significantly inhibit tumor cell growth. We further showed the regulatory role of ts-ARFGEF1 in p53-mediated apoptosis through affecting the PERK/eIF2a/ATF4/CHOP signaling pathway in breast cancer cells. This study thus described both bioinformatics procedures and experimental validation steps for rigorous characterization of transcriptionally non-co-linear RNAs, expanding the discovery of this important but understudied class of RNAs.

bioinformatics↗

bioRxiv2022

SORLA mediates endocytic uptake of proIAPP and protects against islet amyloid deposition

Aims/ hypothesisSorting-related receptor with type A repeats (SORLA) is a neuronal sorting receptor that prevents accumulation of amyloid-beta peptides, the main constituent of senile plaques in Alzheimer disease. Recent transcriptomic studies show that SORLA transcripts are also found in pancreatic islet beta cells, yet the role of SORLA in islets is unclear so far. Based on its protective role in reducing amyloid burden in the brain, we hypothesized that SORLA may have a similar function in the pancreas, regulating islet amyloid plaque formation from islet amyloid polypeptide (IAPP). MethodsWe generated human IAPP transgenic mice lacking SORLA (hIAPP:SORLA KO) to assess the consequences of receptor deficiency for islet histopathology and function in vivo. Using both primary islet cells and established cell lines, we further investigated the molecular mechanisms whereby SORLA controls the cellular metabolism and accumulation of IAPP. ResultsLoss of SORLA activity in hIAPP:SORLA KO resulted in a significant increase in islet amyloid deposits and associated islet cell death as compared to hIAPP:SORLA WT animals expressing the receptor. Aggravated islet amyloid deposition was observed in mice fed a normal chow diet, not requiring high-fat diet feeding typically needed to induce islet amyloidosis in mouse models. Further in vitro studies showed that SORLA binds to and mediates the endocytic uptake of proIAPP, but not mature IAPP, delivering the propeptide to an endolysosomal fate. Conclusions/interpretationSORLA functions as a clearance receptor specific for proIAPP, protecting against islet amyloid deposition and associated cell death caused by IAPP.

cell biology↗

bioRxiv2021

Elevated islet prohormone ratios as indicators of insulin dependency in islet transplant recipients

Autologous pancreatic islet transplantation is an established therapy for patients with chronic pancreatitis. However, the long-term transplant outcomes are modest. Identifying indicators of graft function will aid the preservation of transplanted islets and glycemic control. To this end, we analyzed beta cell prohormone peptide levels in a retrospective cohort of total pancreatectomy autologous islet transplant patients (n=28). Proinsulin-to-C-peptide (PI/C) and proIAPP-to-total IAPP (proIAPP/IAPP) ratios measured at 3 months post-transplant were significantly higher in patients who remained insulin dependent at 1 year follow-up. In a mouse model of human islet transplantation, recipient mice that later became hyperglycemic displayed significantly higher PI/C ratios than mice that remained normoglycemic. Histological analysis of islet grafts showed reduced insulin- and proinsulin-positive area, but elevated glucagon-positive area in grafts that experienced greater secretory demand. Increased prohormone convertase 1/3 was detected in glucagon-positive cells, and glucagon-like peptide 1 (GLP-1) area was elevated in grafts from mice that displayed hyperglycemia or elevated plasma PI/C ratios, demonstrating intra-islet incretin production in metabolically challenged human islet grafts. These data indicate that in failing grafts, alpha cell prohormone processing is likely altered, and incomplete beta cell prohormone processing may be an early indicator of insulin dependency.

pathology↗

bioRxiv2021

Single-cell transcriptomic analysis unveils spinal motor neuron subtype diversity underpinning the water-to-land transition in vertebrates

Spinal motor neurons (MNs) integrate sensory stimuli and brain commands to generate motor movements in vertebrates. Distinct MN populations and their diversity has long been hypothesized to co-evolve with motor circuit to provide the neural basis from undulatory to ambulatory locomotion during aquatic-to-terrestrial transition of vertebrates. However, how these subtypes are evolved remains largely enigmatic. Using single-cell transcriptomics, we investigate heterogeneity in mouse MNs and discover novel segment-specific subtypes. Among limb-innervating MNs, we reveal a diverse neuropeptide code for delineating putative motor pool identities. We further uncovered that axial MNs are subdivided by three conserved and molecularly distinct subpopulations, defined by Satb2, Nr2f2 or Bcl11b expression. Although axial MNs are conserved from cephalochordates to humans, subtype diversity becomes prominent in land animals and appears to continue evolving in humans. Overall, our study provides a unified classification system for spinal MNs and paves the way towards deciphering how neuronal subtypes are evolved.

developmental biology↗

bioRxiv2021

The individuality of shape asymmetries of the human cerebral cortex

Asymmetries of the cerebral cortex are found across diverse phyla and are particularly pronounced in humans, with important implications for brain function and disease. However, many prior studies have confounded asymmetries due to size with those due to shape. Here, we introduce a novel approach to characterize asymmetries of the whole cortical shape, independent of size, across different spatial frequencies using magnetic resonance imaging data in three independent datasets. We find that cortical shape asymmetry is highly individualized and robust, akin to a cortical fingerprint, and identifies individuals more accurately than size-based descriptors, such as cortical thickness and surface area, or measures of inter-regional functional coupling of brain activity. Individual identifiability is optimal at coarse spatial scales ([~]37 mm wavelength), and shape asymmetries show scale-specific associations with sex and cognition, but not handedness. While unihemispheric cortical shape shows significant heritability at coarse scales ([~]65 mm wavelength), shape asymmetries are determined primarily by subject-specific environmental effects. Thus, coarse-scale shape asymmetries are highly personalized, sexually dimorphic, linked to individual differences in cognition, and are primarily driven by stochastic environmental influences.

neuroscience↗

bioRxiv2021

How big should this object be? Perceptual influences on viewing-size preferences

When viewing objects depicted in a frame, observers prefer to view large objects like cars in larger sizes and smaller objects like cups in smaller sizes. That is, the visual size of an object that "looks best" is linked to its typical physical size in the world. Why is this the case? One intuitive possibility is that these preferences are driven by semantic knowledge: For example, when we recognize a sofa, we access our knowledge about its real-world size, and this influences what size we prefer to view the sofa within a frame. However, might visual processing play a role in this phenomenon--that is, do visual features that are related to big and small objects look better at big and small visual sizes, respectively, even when observers do not have explicit access to semantic knowledge about the objects? To test this possibility, we used "texform" images, which are synthesized versions of recognizable objects, which critically retain local perceptual texture and coarse contour information, but are no longer explicitly recognizable. To test for visual size preferences, we first used a size adjustment task, and the results were equivocal. However, clear results were obtained using a two-interval forced choice task, in which each texform was presented at the preferred visual size of its corresponding original image, and a visual size slightly bigger or smaller. Observers consistently selected the texform presented at the canonical visual size as the more aesthetically pleasing one. An additional control experiment ruled out alternative explanations related to size priming effects. These results suggest that the preferred visual size of an object depends not only on explicit knowledge of its real-world size, but also can be evoked by mid-level visual features that systematically covary with an objects real-world size. HighlightsO_LIWe prefer to view large objects like cars large, and small objects like cups small C_LIO_LIIntuitively, such preferences may be driven by our knowledge of object sizes C_LIO_LIWe used unrecognizable texforms of objects that preserved mid-level visual features C_LIO_LISimilar viewing size preferences can be revealed with these texforms C_LIO_LISuch preferences thus arise not only from knowledge but also from visual processing C_LI

animal behavior and cognition↗

bioRxiv2021

Disruption of VGLUT1 in cholinergic medial habenula projections increases nicotine self-administration

Cholinergic projections from the medial habenula (MHb) to the interpeduncular nucleus (IPN) have been studied for their complex contributions to nicotine addiction and have been implicated in nicotine reinforcement, aversion, and withdrawal. While it has been established that MHb cholinergic projections co-release glutamate, no direct evidence has demonstrated a role for this specific glutamate projection in nicotine consumption. In the present study, a novel floxed Slc17a7 (VGLUT1) mouse was generated and used to create conditional knockout (cKO) mice that lack VGLUT1 in MHb cholinergic neurons. Histochemical approaches and optogenetics-assisted electrophysiology were used to validate the disruption of VGLUT1 from cholinergic MHb to IPN projections. The mice displayed no gross phenotypic abnormalities and exhibited normal exploratory and locomotor behavior in the open-field assay. However, the loss of VGLUT1-mediated glutamate co-release led to increased nicotine self-administration. These findings indicate that glutamate co-release from ventral MHb cholinergic neurons opposes nicotine consumption and provide additional support for targeting this synapse to develop potential treatments to nicotine addiction.

neuroscience↗

bioRxiv2021

A comprehensive series of temporal transcription factors in the fly visual system

The brain consists of thousands of different neuronal types that are generated through multiple divisions of neuronal stem cells. These stem cells have the capacity to generate different neuronal types at different stages of their development. In Drosophila, this temporal patterning is driven by the successive expression of temporal transcription factors (tTFs). While a number of tTFs are known in different animals and across various parts of the nervous system, these have been mostly identified by informed guesses and antibody availability. We used single-cell mRNA sequencing to identify the complete series of tTFs that specify most Drosophila medulla neurons in the optic lobe. We tested the genetic interactions among these tTFs. While we verify the general principle that tTFs regulate the progression of the series by activating the next tTFs in the series and repressing the previous ones, we also identify more complex regulations. Two of the tTFs, Eyeless and Dichaete, act as hubs integrating the input of several upstream tTFs before allowing the series to progress and in turn regulating the expression of several downstream tTFs. Moreover, we show that tTFs not only specify neuronal identity by controlling the expression of cell type-specific genes. Finally, we describe the very first steps of neuronal differentiation and find that terminal differentiation genes, such as neurotransmitter-related genes, are present as transcripts, but not as proteins, in immature larval neurons days before they are being used in functioning neurons; we show that these mechanisms are conserved in humans. Our results offer a comprehensive description of a temporal series of tTFs in a neuronal system, offering mechanistic insights into the regulation of the progression of the series and the regulation of neuronal diversity. This represents a proof-of-principle for the use of single-cell mRNA sequencing for the comparison of temporal patterning across phyla that can lead to an understanding of how the human brain develops and how it has evolved.

developmental biology↗

bioRxiv2021

Modeling SARS-CoV-2 and Influenza Infections and Antiviral Treatments in Human Lung Epithelial Tissue Equivalents

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the third coronavirus in less than 20 years to spillover from an animal reservoir and cause severe disease in humans. High impact respiratory viruses such as pathogenic beta-coronaviruses and influenza viruses, as well as other emerging respiratory viruses, pose an ongoing global health threat to humans. There is a critical need for physiologically relevant, robust and ready to use, in vitro cellular assay platforms to rapidly model the infectivity of emerging respiratory viruses and discover and develop new antiviral treatments. Here, we validate in vitro human alveolar and tracheobronchial tissue equivalents and assess their usefulness as in vitro assay platforms in the context of live SARS-CoV-2 and influenza A virus infections. We establish the cellular complexity of two distinct tracheobronchial and alveolar epithelial air liquid interface (ALI) tissue models, describe SARS-CoV-2 and influenza virus infectivity rates and patterns in these ALI tissues, the viral-induced cytokine production as it relates to tissue-specific disease, and demonstrate the pharmacologically validity of these lung epithelium models as antiviral drug screening assay platforms.

microbiology↗

bioRxiv2021

Angiopoietin 1 and integrin beta 1b are vital for zebrafish brain development

This study aimed at identifying the role of angiopoietin 1 (angpt1) in brain development, the mode of action of angpt1, and the main targets in the zebrafish brain. We investigated embryonic brain angiogenesis and neural development in the angpt1sa14264, itgb1bmi371, tekhu1667 mutant fish, and the effects of transgenic overexpression of angpt1 in the larval brain. Lack of angpt1 was associated with downregulation of tek and upregulation of itgb1b. We found deficiencies in the patterning of proliferation, the vascular network and reticulospinal neurons in the hindbrain, and selective deficiencies in specific neurotransmitter systems. In the angpt1sa14264 and itgb1bmi371 larval brains, using microangiography, retrograde labeling, and immunostaining, we demonstrated that the targeted destruction of angpt1sa14264 and itgb1bmi371 mutant fish caused severe irregular cerebrovascular development, aberrant hindbrain patterning, downregulation of neural proliferation, expansion of the radial glial progenitors, deficiencies of dopaminergic, histaminergic, and GABAergic populations in the larval brain. In contrast, the tekhu1667 mutants regularly grew with no such apparent phenotypes. Neurally overexpressed angpt1 promoted opposite effects by increasing the vascular branching, increasing cell proliferation, and neuronal progenitors. Notably, zebrafish angpt1 showed neurogenic activity independent of its typical receptor tek, indicating the novel role of a dual regulation by angpt1 in embryonic neurogenesis and angiogenesis in zebrafish. The results show that angpt1 and its interaction with itgb1b are crucial in zebrafish brain neuronal and vascular development and suggest that angpt1 through itgb1b can act as a neurogenic factor in the neural proliferation fate in the developing brain.

neuroscience↗

bioRxiv2021

Comprehensive Assessment of Somatic Copy Number Variation Calling Using Next-Generation Sequencing Data

Copy number variation (CNV) is a common type of mutation that often drives cancer progression. With advances in next-generation sequencing (NGS), CNVs can be detected in a detailed manner via newly developed computational tools but quality of such CNV calls has not been carefully evaluated. We analyzed CNV calls reported by 6 cutting-edge callers for 91 samples which were derived from the same cancer cell line, prepared and sequenced by varying the following factors: type of tissue sample (Fresh vs. Formalin Fixed Paraffin Embedded (FFPE)), library DNA amount, tumor purity, sequencing platform (Whole-Genome Sequencing (WGS) versus Whole-Exome Sequencing (WES)), and sequencing coverage. We found that callers greatly determined the pattern of CNV calls. Calling quality was drastically impaired by low purity (<50%) and became variable when WES, FFPE, and medium purity (50%-75%) were applied. Effects of low DNA amount and low coverage were relatively minor. Our analysis demonstrates the limitation of benchmarking somatic CNV callers when the real ground truth is not available. Our comprehensive analysis has further characterized each caller with respect to confounding factors and examined the consistency of CNV calls, thereby providing guidelines for conducting somatic CNV analysis.

bioinformatics↗

bioRxiv2021

Single Cell Biological Microlasers Powered by Deep Learning

Cellular lasers are cutting-edge technologies for biomedical applications. Due to the enhanced interactions between light and cells in microcavities, cellular properties and subtle changes of cells can be significantly reflected by the laser emission characteristics. In particular, transverse laser modes from single-cell lasers which utilize Fabry-Perot cavities are highly correlated to the spatial biophysical properties of cells. However, the high chaotic and complex variation of laser modes limits their practical applications for cell detections. Deep learning technique has demonstrated its powerful capability in solving complex imaging problems, which is expected to be applied for cell detections based on laser mode imaging. In this study, deep learning technique was applied to analyze laser modes generated from single-cell lasers, in which a correlation between laser modes and physical properties of cells was built. As a proof-of-concept, we demonstrated the predictions of cell sizes using deep learning based on laser mode imaging. In the first part, bioinspired cell models were fabricated to systematically study how cell sizes affect the characteristics of laser modes. By training a convolutional neuron network (CNN) model with laser mode images, predictions of cell model diameters with a sub-wavelength accuracy were achieved. In the second part, deep learning was employed to study laser modes generated from biological cells. By training a CNN model with laser mode images acquired from astrocyte cells, predictions of cell sizes with a sub-wavelength accuracy were also achieved. The results show the great potential of laser mode imaging integrated with deep learning for cell analysis and biophysical studies.

biophysics↗

bioRxiv2020

A Synthetic Transcription Platform for Programmable Gene Expression in Mammalian Cells

Precise, scalable, and sustainable control of genetic and cellular activities in mammalian cells is key to developing precision therapeutics and smart biomanufacturing. We created a highly tunable, modular, versatile CRISPR-based synthetic transcription system for the programmable control of gene expression and cellular phenotypes in mammalian cells. Genetic circuits consisting of well-characterized libraries of guide RNAs, binding motifs of synthetic operators, transcriptional activators, and additional genetic regulatory elements expressed mammalian genes in a highly predictable and tunable manner. We demonstrated the programmable control of reporter genes episomally and chromosomally, with up to 25-fold more activity than seen with the EF1 promoter, in multiple cell types. We used these circuits to program the secretion of human monoclonal antibodies and to control T-cell effector function marked by interferon-{gamma} production. Antibody titers and interferon-{gamma} concentrations significantly correlated with synthetic promoter strengths, providing a platform for programming gene expression and cellular function in diverse applications.

synthetic biology↗

bioRxiv2020

Glucolipotoxicity-induced Mig6 desensitizes EGFR signaling and promotes pancreatic beta cell death

A loss of functional beta cell mass is a final etiological event in the development of frank type 2 diabetes (T2D). To preserve or expand beta cells and therefore treat/prevent T2D, growth factors have been considered therapeutically but have largely failed to achieve robust clinical success. The molecular mechanisms preventing the activation of mitogenic signaling pathways from maintaining functional beta cell mass during the development of T2D remain unknown. We speculated that endogenous negative effectors of mitogenic signaling cascades impede beta cell survival/expansion. Thus, we tested the hypothesis that a stress-inducible epidermal growth factor receptor (EGFR) inhibitor, Mitogen-inducible gene 6 (Mig6), regulates beta cell fate in a T2D milieu. To this end, we determined that: 1) glucolipotoxicity (GLT) induces Mig6, thereby blunting EGFR signaling cascades, and 2) Mig6 mediates molecular events regulating beta cell survival/death. We discovered that GLT impairs EGFR activation, and Mig6 is elevated in human islets from T2D donors as well as GLT-treated rodent islets and 832/13 INS-1 beta cells. Mig6 is essential for GLT-induced EGFR desensitization, as Mig6 suppression rescued the GLT-impaired EGFR and ERK1/2 activation. Further, Mig6 mediated EGFR but not insulin-like growth factor-1 receptor nor hepatocyte growth factor receptor activity in beta cells. Finally, we identified that elevated Mig6 augmented beta cell apoptosis, as Mig6 suppression reduced apoptosis during GLT. In conclusion, we established that T2D and GLT induce Mig6 in pancreatic beta cells. The elevated Mig6 desensitizes EGFR signaling and induces beta cell death. Our findings suggest that Mig6 could be a novel therapeutic target for T2D, as blocking Mig6 could possibly enhance mitogenic signaling cascades in a diabetic milieu to promote beta cell survival and prevent beta cell death.

cell biology↗