Marked enhancement of the immunogenicity of plant-expressed IgG-Fc fusion proteins by inclusion of cholera toxin non-toxic B subunit within the single polypeptide.

Immunoglobulin G (IgG)-based fusion proteins have been widely exploited as a potential vaccine delivery platform but in the absence of exogenous adjuvants, the lack of robust immunity remains an obstacle. Here, we report on a key modification that overcomes that obstacle. Thus, we constructed an IgG-Fc vaccine platform for dengue, termed D-PCF, which in addition to a dengue antigen incorporates the cholera toxin non-toxic B subunit (CTB) as a molecular adjuvant, with all three proteins expressed as a single polypeptide. Following expression in Nicotiana benthamiana plants, the D-PCF assembled as polymeric structures of similar size to human IgM, a process driven by the pentamerization of CTB. A marked improvement of functional properties in vitro and immunogenicity in vivo over a previous iteration of the Fc-fusion protein without CTB [1] was demonstrated. These include enhanced antigen presenting cell binding, internalization and activation, complement activation, epithelial cell interactions and ganglioside binding, as well as more efficient polymerization within the expression host. Following immunization of mice with D-PCF by a combination of systemic and mucosal (intranasal) routes, we observed robust systemic and mucosal immune responses, as well as systemic T cell responses, significantly higher than those induced by a related Fc-fusion protein but without CTB. The induced antibodies could bind to the domain III of the dengue virus envelope protein from all four dengue serotypes. Finally, we also demonstrated feasibility of aerosolization of D-PCF as a prerequisite for vaccine delivery by the respiratory route.

A Comparative Analysis of Various Machine Learning Algorithms to Improve the Accuracy of HbA1c Estimation Using Wrist PPG Data.

Due to the inconvenience of drawing blood and the possibility of infection associated with invasive methods, research on non-invasive glycated hemoglobin (HbA1c) measurement methods is increasing. Utilizing wrist photoplethysmography (PPG) with machine learning to estimate HbA1c can be a promising method for non-invasive HbA1c monitoring in diabetic patients. This study aims to develop a HbA1c estimation system based on machine learning algorithms using PPG signals obtained from the wrist. We used a PPG based dataset of 22 subjects and algorithms such as extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), Categorical Boost (CatBoost) and random forest (RF) to estimate the HbA1c values. Note that the AC-to-DC ratios for three wavelengths were newly adopted as features in addition to the previously acquired 15 features from the PPG signal and a comparative analysis was performed between the performances of several algorithms. We showed that feature-importance-based selection can improve performance while reducing computational complexity. We also showed that AC-to-DC ratio (AC/DC) features play a dominant role in improving HbA1c estimation performance and, furthermore, a good performance can be obtained without the need for external features such as BMI and SpO2. These findings may help shape the future of wrist-based HbA1c estimation (e.g., via a wristwatch or wristband), which could increase the scope of noninvasive and effective monitoring techniques for diabetic patients.

Plant-derived human recombinant growth factors and serum albumin maintain stemness of human-induced pluripotent stem cells.

Stem cells are an important therapeutic source for recovery and regeneration, as their ability of self-renewal and differentiation offers an unlimited supply of highly specialized cells for therapeutic transplantation. Growth factors and serum are essential for maintaining the characteristics of stem cells in culture and for inducing differentiation. Because growth factors are produced mainly in bacterial (Escherichia coli) or animal cells, the use of such growth factors raises safety concerns that need to be resolved for the commercialization of stem cell therapeutics. To overcome this problem, studies on proteins produced in plants have been conducted. Here, we describe the functions of plant-derived fibroblast growth factor 2 (FGF2) and human serum albumin in the maintenance and differentiation of human-induced pluripotent stem cells (hiPSCs). Plant-derived FGF2 and human epidermal growth factor EGF were able to differentiate hiPSCs into neural stem cells (NSCs). These NSCs could differentiate into neuronal and glial cells. Our results imply that culturing stem cells in animal-free culture medium, which is composed of plant-derived proteins, would facilitate stem cell application research, for example, for cell therapy, by reducing contamination risk.

Machine-Learning-Based Noninvasive In Vivo Estimation of HbA1c Using Photoplethysmography Signals.

Glycated hemoglobin (HbA1c) is an important factor in monitoring diabetes. Since the glycated hemoglobin value reflects the average blood glucose level over 3 months, it is not affected by exercise or food intake immediately prior to measurement. Thus, it is used as the most basic measure of evaluating blood-glucose control over a certain period and predicting the occurrence of long-term complications due to diabetes. However, as the existing measurement methods are invasive, there is a burden on the measurement subject who has to endure increased blood gathering and exposure to the risk of secondary infections. To overcome this problem, we propose a machine-learning-based noninvasive estimation method in this study using photoplethysmography (PPG) signals. First, the development of the device used to acquire the PPG signals is described in detail. Thereafter, discriminative and effective features are extracted from the acquired PPG signals using the device, and a machine-learning algorithm is used to estimate the glycated hemoglobin value from the extracted features. Finally, the performance of the proposed method is evaluated by comparison with existing model-based methods.

Optical Measurement of Molar Absorption Coefficient of HbA1c: Comparison of Theoretical and Experimental Results.

Diabetes can cause dangerous complications if not diagnosed in a timely manner. The World Health Organization accepts glycated hemoglobin (HbA1c) as a measure of diagnosing diabetes as it provides significantly more information on the glycemic behavior from a single blood sample than the fasting blood sugar reading. The molar absorption coefficient of HbA1c is needed to quantify the amount of HbA1c present in a blood sample. In this study, we measured the molar absorption coefficient of HbA1c in the range of 450 nm to 700 nm using optical methods experimentally. We observed that the characteristic peaks of the molar absorption coefficient of HbA1c (at 545 nm and 579 nm for level 1, at 544 nm and 577 nm for level 2) are in close agreement with those reported in previous studies. The molar absorption coefficient values were also found to be close to those of earlier reports. The average molar absorption coefficient values of HbA1c were found to be 804,403.5 M−1cm−1 at 545 nm and 703,704.5 M−1cm−1 at 579 nm for level 1 as well as 503,352.4 M−1cm−1 at 544 nm and 476,344.6 M−1cm−1 at 577 nm for level 2. Our experiments focused on calculating the molar absorption coefficients of HbA1c in the visible wavelength region, and the proposed experimental method has an advantage of being able to easily obtain the molar absorption coefficient at any wavelength in the visible wavelength region. The results of this study are expected to help future investigations on noninvasive methods of estimating HbA1c levels.

Cuffless Blood Pressure Estimation Based on Monte Carlo Simulation Using Photoplethysmography Signals.

Blood pressure measurements are one of the most routinely performed medical tests globally. Blood pressure is an important metric since it provides information that can be used to diagnose several vascular diseases. Conventional blood pressure measurement systems use cuff-based devices to measure the blood pressure, which may be uncomfortable and sometimes burdensome to the subjects. Therefore, in this study, we propose a cuffless blood pressure estimation model based on Monte Carlo simulation (MCS). We propose a heterogeneous finger model for the MCS at wavelengths of 905 nm and 940 nm. After recording the photon intensities from the MCS over a certain range of blood pressure values, the actual photoplethysmography (PPG) signals were used to estimate blood pressure. We used both publicly available and self-made datasets to evaluate the performance of the proposed model. In case of the publicly available dataset for transmission-type MCS, the mean absolute errors are 3.32 ± 6.03 mmHg for systolic blood pressure (SBP), 2.02 ± 2.64 mmHg for diastolic blood pressure (DBP), and 1.76 ± 2.8 mmHg for mean arterial pressure (MAP). The self-made dataset is used for both transmission- and reflection-type MCSs; its mean absolute errors are 2.54 ± 4.24 mmHg for SBP, 1.49 ± 2.82 mmHg for DBP, and 1.51 ± 2.41 mmHg for MAP in the transmission-type case as well as 3.35 ± 5.06 mmHg for SBP, 2.07 ± 2.83 mmHg for DBP, and 2.12 ± 2.83 mmHg for MAP in the reflection-type case. The estimated results of the SBP and DBP satisfy the requirements of the Association for the Advancement of Medical Instrumentation (AAMI) standards and are within Grade A according to the British Hypertension Society (BHS) standards. These results show that the proposed model is efficient for estimating blood pressures using fingertip PPG signals.

Deep-Learning-Based Adaptive Symbol Decision for Visual MIMO System with Variable Channel Modeling.

A channel modeling method and deep-learning-based symbol decision method are proposed to improve the performance of a visual MIMO system for communication between a variable-color LED array and camera. Although image processing algorithms using color clustering are available to correct distorted color information in a channel, color-similarity-based approaches are limited by real-world distortions; to overcome such limitations, symbol decision is defined as a multiclass classification problem. Further, to learn a robust classifier against channel distortion, a deep neural network learning technique is applied to adaptively determine symbols from channel distortion. The network designed herein comprises the channel identification and symbol decision modules; the channel identification module extracts a channel identification vector for symbol determination from an input image using a two-dimensional deep convolutional neural network (CNN); the symbol decision module then generates a feature map by combining the channel identification vector and information on adjacent symbols to determine the symbol via learning correlations between adjacent symbols using a one-dimensional CNN. The two modules are connected together and learned simultaneously in an end-to-end manner. We also propose a new channel modeling method that intuitively reflects real-world distortion factors rather than the conventional additive white Gaussian noise channel to efficiently train deep-learning networks. Lastly, in the proposed channel distortion environment, the proposed method shows performance improvement by an average of about 41.8% (up to about 54.8%) compared to the existing Euclidean distance method, and about 6.3% (up to about 9.2%) on average compared to the SVM method.

Noninvasive In Vivo Estimation of Blood-Glucose Concentration by Monte Carlo Simulation.

Continuous monitoring of blood-glucose concentrations is essential for both diabetic and nondiabetic patients to plan a healthy lifestyle. Noninvasive in vivo blood-glucose measurements help reduce the pain of piercing human fingertips to collect blood. To facilitate noninvasive measurements, this work proposes a Monte Carlo photon simulation-based model to estimate blood-glucose concentration via photoplethysmography (PPG) on the fingertip. A heterogeneous finger model was exposed to light at 660 nm and 940 nm in the reflectance mode of PPG via Monte Carlo photon propagation. The bio-optical properties of the finger model were also deduced to design the photon simulation model for the finger layers. The intensities of the detected photons after simulation with the model were used to estimate the blood-glucose concentrations using a supervised machine-learning model, XGBoost. The XGBoost model was trained with synthetic data obtained from the Monte Carlo simulations and tested with both synthetic and real data (n = 35). For testing with synthetic data, the Pearson correlation coefficient (Pearson's r) of the model was found to be 0.91, and the coefficient of determination (R2) was found to be 0.83. On the other hand, for tests with real data, the Pearson's r of the model was 0.85, and R2 was 0.68. Error grid analysis and Bland-Altman analysis were also performed to confirm the accuracy. The results presented herein provide the necessary steps for noninvasive in vivo blood-glucose concentration estimation.

CityGML urban model generation using national public datasets for flood damage simulations: A case study in Korea.

Managing information at city level has become increasingly important owing to the introduction of smart cities and the increasing severity of disasters due to climate change. A data collection framework, model construction, and information management must be established to systematically manage information at the city level. This study developed an urban model generation method using detailed attributes within the City Geography Markup Language (CityGML), a standard data schema for 3D representation of cities based on different types of publicly available information within Korea. The generated model was used to develop a method for simulating flooding status, degree of flooding, and level of building damage after heavy rainfall, in Korea. Furthermore, we developed a method to estimate the loss of human life and property damage by combining the results of the flood analysis with the city model. The proposed methodology supports the creation of standard-based models for flood analysis and exhibits strong interoperability for application to different areas of analysis.

Local supplementation with plant-derived recombinant human FGF2 protein enhances bone formation in critical-sized calvarial defects.

Numerous studies have demonstrated the advantages of plant cell suspension culture systems in producing bioactive recombinant human growth factors. This study investigated the biological activity of recombinant basic human fibroblast growth factor (rhFGF2) protein produced by a plant culture system to enhance new bone formation in a bone defect mouse model. The human FGF2 cDNA gene was cloned into a plant expression vector driven by the rice α-amylase 3D promoter. The vector was introduced into rice calli (Oryza sativa L. cv. Dongjin), and the clone with the highest expression of rhFGF2 was selected. Maximum accumulation of rhFGF2 protein (approximately 28 mg/l) was reached at 13 day post-incubation. Male C57BL/6 mice underwent calvarial defect surgery and the defects were loaded with absorbable collagen sponge (ACS) only (ACS group) or ACS impregnated with 5 µg of plant-derived rhFGF2 (p-FGF2) protein or E. coli-derived rhFGF2 (e-FGF2) protein. Similar to the effects of e-FGF2, local delivery with p-FGF2 enhanced bone healing in the damaged region to higher levels than the ACS group. Exogenous addition of p-FGF2 or e-FGF2 exhibited similar effects on proliferation, mineralization, and osteogenic marker expression in MC3T3-E1 cells. Together, the current findings support the usefulness of this plant-based expression system for the production of biologically active rhFGF2.

Time-Sharing-Based Synchronization and Performance Evaluation of Color-Independent Visual-MIMO Communication.

In the field of communication, synchronization is always an important issue. The communication between a light-emitting diode (LED) array (LEA) and a camera is known as visual multiple-input multiple-output (MIMO), for which the data transmitter and receiver must be synchronized for seamless communication. In visual-MIMO, LEDs generally have a faster data rate than the camera. Hence, we propose an effective time-sharing-based synchronization technique with its color-independent characteristics providing the key to overcome this synchronization problem in visual-MIMO communication. We also evaluated the performance of our synchronization technique by varying the distance between the LEA and camera. A graphical analysis is also presented to compare the symbol error rate (SER) at different distances.

Reduced paucimannosidic N-glycan formation by suppression of a specific ß-hexosaminidase from Nicotiana benthamiana.

Plants are attractive hosts for the production of recombinant glycoproteins for therapeutic use. Recent advances in glyco-engineering facilitate the elimination of nonmammalian-type glycosylation and introduction of missing pathways for customized N-glycan formation. However, some therapeutically relevant recombinant glycoproteins exhibit unwanted truncated (paucimannosidic) N-glycans that lack GlcNAc residues at the nonreducing terminal end. These paucimannosidic N-glycans increase product heterogeneity and may affect the biological function of the recombinant drugs. Here, we identified two enzymes, ß-hexosaminidases (HEXOs) that account for the formation of paucimannosidic N-glycans in Nicotiana benthamiana, a widely used expression host for recombinant proteins. Subcellular localization studies showed that HEXO1 is a vacuolar protein and HEXO3 is mainly located at the plasma membrane in N. benthamiana leaf epidermal cells. Both enzymes are functional and can complement the corresponding HEXO-deficient Arabidopsis thaliana mutants. In planta expression of HEXO3 demonstrated that core α1,3-fucose enhances the trimming of GlcNAc residues from the Fc domain of human IgG. Finally, using RNA interference, we show that suppression of HEXO3 expression can be applied to increase the amounts of complex N-glycans on plant-produced human α1-antitrypsin.

Induction of immune responses in mice and pigs by oral administration of classical swine fever virus E2 protein expressed in rice calli.

Classical swine fever (CSF), caused by the CSF virus (CSFV), is a highly contagious disease in pigs. In Korea, vaccination using a live-attenuated strain (LOM strain) has been used to control the disease. However, parenteral vaccination using a live-attenuated strain still faces a number of problems related to storage, cost, injection stress, and differentiation of CSFV infected and vaccinated pigs. Therefore, two kinds of new candidates for oral vaccination have been developed based on the translation of the E2 gene of the SW03 strain, which was isolated from an outbreak of CSF in 2002 in Korea, in transgenic rice calli (TRCs) from Oriza sativa L. cv. Dongjin to express a recombinant E2 protein (rE2-TRCs). The expression of the recombinant E2 protein (rE2) in rE2-TRCs was confirmed using Northern blot, SDS-PAGE, and Western blot analysis. Immune responses to the rE2-TRC in mice and pigs were investigated after oral administration. The administration of rE2-TRCs increased E2-specific antibodies titers and antibody-secreting cells when compared to animals receiving the vector alone (p < 0.05 and p < 0.01). In addition, mice receiving rE2-TRCs had a higher level of CD8+ lymphocytes and Th1 cytokine immune responses to purified rE2 (prE2) in vitro than the controls (p < 0.05 and p < 0.01). Pigs receiving rE2-TRCs also showed an increase in IL-8, CCL2, and the CD8+ subpopulation in response to stimulation with prE2. These results suggest that oral administration of rE2-TRCs can induce E2-specific immune responses.

Biopotentials of Collagen Scaffold Impregnated with Plant-Cell-Derived Epidermal Growth Factor in Defective Bone Healing.

The combination of scaffolds with recombinant human epidermal growth factor (rhEGF) protein can enhance defective bone healing via synergistic activation to stimulate cellular growth, differentiation, and survival. We examined the biopotentials of an rhEGF-loaded absorbable collagen scaffold (ACS) using a mouse model of calvarial defects, in which the rhEGF was produced from a plant cell suspension culture system because of several systemic advantages. Here, we showed a successful and large-scale production of plant-cell-derived rhEGF protein (p-rhEGF) by introducing an expression vector that cloned with its cDNA under the control of rice α-amylase 3D promoter into rice calli (Oryza sativa L. cv. Dongjin). Implantation with p-rhEGF (5 µg)-loaded ACSs into critical-sized calvarial defects enhanced new bone formation and the expression of osteoblast-specific markers in the defected regions greater than implantation with ACSs alone did. The potency of p-rhEGF-induced bone healing was comparable with that of Escherichia coli-derived rhEGF protein. The exogenous addition of p-rhEGF increased the proliferation of human periodontal ligament cells and augmented the induction of interleukin 8, bone morphogenetic protein 2, and vascular endothelial growth factor in the cells. Collectively, this study demonstrates the successful and convenient production of p-rhEGF, as well as its potency to enhance ACS-mediated bone regeneration by activating cellular responses that are required for wound healing.

Reactive oxygen species mediated DNA damage is essential for abnormal erythropoiesis in peroxiredoxin II(-/-) mice.

Erythroid cells are highly prone to oxidative damage generated during erythropoiesis and thus are well equipped with antioxidant defense systems. However, their roles have been poorly characterized. Here, we investigated the role of peroxiredoxin II in mouse erythropoiesis. Loss of Prx II significantly increased apoptosis and cell cycle arrest leading to abnormal erythropoiesis at 3 weeks of age when erythropoietin levels were almost same between wild type and Prx II(-/-). In Prx II(-/-) bone marrow cells, DNA tail length as an indicator of the oxidative damage was greatly increased and mRNAs of the molecules associated with DNA damage and repair and transcription regulators of antioxidant enzymes were also significantly increased. In addition, N-Acetyl-L-Cysteine treatment significantly decreased immature erythroblasts and apoptotic cells increased in Prx II(-/-) BMCs. These results strongly demonstrate that Prx II plays an essential role in maintaining normal erythropoiesis by protecting DNA damage.

Peroxiredoxin II is essential for preventing hemolytic anemia from oxidative stress through maintaining hemoglobin stability.

The pathophysiology of oxidative hemolytic anemia is closely associated with hemoglobin (Hb) stability; however, the mechanism of how Hb maintains its stability under oxidative stress conditions of red blood cells (RBCs) carrying high levels of oxygen is unknown. Here, we investigated the potential role of peroxiredoxin II (Prx II) in preventing Hb aggregation induced by reactive oxygen species (ROS) using Prx II knockout mice and RBCs of patients with hemolytic anemia. Upon oxidative stress, ROS and Heinz body formation were significantly increased in Prx II knockout RBCs compared to wild-type (WT), which ultimately accelerated the accumulation of hemosiderin and heme-oxygenase 1 in the Prx II knock-out livers. In addition, ROS-dependent Hb aggregation was significantly increased in Prx II knockout RBCs. Interestingly, Prx II interacted with Hb in mouse RBCs, and their interaction, in particular, was severely impaired in RBCs of patients with thalassemia (THAL) and sickle cell anemia (SCA). Hb was bound to the decameric structure of Prx II, by which Hb was protected from oxidative stress. These findings suggest that Prx II plays an important role in preventing hemolytic anemia from oxidative stress by binding to Hb as a decameric structure to stabilize it.

Production of recombinant human granulocyte macrophage-colony stimulating factor in rice cell suspension culture with a human-like N-glycan structure.

The rice α-amylase 3D promoter system, which is activated under sucrose-starved conditions, has emerged as a useful system for producing recombinant proteins. However, using rice as the production system for therapeutic proteins requires modifications of the N-glycosylation pattern because of the potential immunogenicity of plant-specific sugar residues. In this study, glyco-engineered rice were generated as a production host for therapeutic glycoproteins, using RNA interference (RNAi) technology to down-regulate the endogenous α-1,3-fucosyltransferase (α-1,3-FucT) and ß-1,2-xylosyltransferase (ß-1,2-XylT) genes. N-linked glycans from the RNAi lines were identified, and their structures were compared with those isolated from a wild-type cell suspension. The inverted-repeat chimeric RNA silencing construct of α-1,3-fucosyltransferase and ß-1,2-xylosyltransferase (Δ3FT/XT)-9 glyco-engineered line with significantly reduced core α-1,3-fucosylated and/or ß-1,2-xylosylated glycan structures was established. Moreover, levels of plant-specific α-1,3-fucose and/or ß-1,2-xylose residues incorporated into recombinant human granulocyte/macrophage colony-stimulating factor (hGM-CSF) produced from the N44 + Δ3FT/XT-4 glyco-engineered line co-expressing ihpRNA of Δ3FT/XT and hGM-CSF were significantly decreased compared with those in the previously reported N44-08 transgenic line expressing hGM-CSF. None of the glyco-engineered lines differed from the wild type with respect to cell division, proliferation or ability to secrete proteins into the culture medium.

Production of functional recombinant bovine trypsin in transgenic rice cell suspension cultures.

A synthetic bovine trypsinogen (sbTrypsinogen) was synthesized on the basis of rice-optimized codon usage via an overlap PCR strategy, prior to being expressed under the control of the sucrose starvation-inducible rice α-amylase 3D (RAmy3D) promoter. Secretion of trypsin into the culture medium was achieved by using the existing signal peptide. The plant expression vector was introduced into rice calli (Oryza sativa L. cv. Dongjin), mediated by Agrobacterium tumefaciens. The integration of the sbTrypsinogen gene into the chromosome of the transgenic rice callus was verified via genomic DNA PCR amplification, and sbTrypsin expression in transgenic rice suspension cells was confirmed via Northern blot analysis. Western blot analysis detected glycosylated proteins in the culture medium, having masses from 24 to 26 kDa, following induction by sugar starvation. Proteolytic activity of the rice-derived trypsin was confirmed by gelatin zymogram, and was similar to that of the commercial bovine-produced trypsin. The yields of sbTrypsin that accumulated in the transgenic rice cell suspension medium were 15 mg/L at 5 days after sugar starvation.

Derivation and validation of gray-box models to estimate noninvasive in-vivo percentage glycated hemoglobin using digital volume pulse waveform.

Glycated hemoglobin and blood oxygenation are the two most important factors for monitoring a patient's average blood glucose and blood oxygen levels. Digital volume pulse acquisition is a convenient method, even for a person with no previous training or experience, can be utilized to estimate the two abovementioned physiological parameters. The physiological basis assumptions are utilized to develop two-finger models for estimating the percent glycated hemoglobin and blood oxygenation levels. The first model consists of a blood-vessel-only hypothesis, whereas the second model is based on a whole-finger model system. The two gray-box systems were validated on diabetic and nondiabetic patients. The mean absolute errors for the percent glycated hemoglobin (%HbA1c) and percent oxygen saturation (%SpO2) were 0.375 and 1.676 for the blood-vessel model and 0.271 and 1.395 for the whole-finger model, respectively. The repeatability analysis indicated that these models resulted in a mean percent coefficient of variation (%CV) of 2.08% and 1.74% for %HbA1c and 0.54% and 0.49% for %SpO2 in the respective models. Herein, both models exhibited similar performances (HbA1c estimation Pearson's R values were 0.92 and 0.96, respectively), despite the model assumptions differing greatly. The bias values in the Bland-Altman analysis for both models were - 0.03 ± 0.458 and - 0.063 ± 0.326 for HbA1c estimation, and 0.178 ± 2.002 and - 0.246 ± 1.69 for SpO2 estimation, respectively. Both models have a very high potential for use in real-world scenarios. The whole-finger model with a lower standard deviation in bias and higher Pearson's R value performs better in terms of higher precision and accuracy than the blood-vessel model.

Systemic and Oral Immunogenicity of Porcine Epidemic Diarrhea Virus Antigen Fused to Poly-Fc of Immunoglobulin G and Expressed in ΔXT/FT Nicotiana benthamiana Plants.

Porcine epidemic diarrhea virus (PEDV), a member of the Coronaviridae family has become increasingly probelmatic in the pig farming industry. Currently, there are no effective, globally applicable vaccines against PEDV. Here, we tested a recombinant PEDV vaccine candidate based on the expression of the core neutralising epitope (COE) of PEDV conjugated to polymeric immunoglobulin G scaffold (PIGS) in glycoengineered Nicotiana be nthamiana plants. The biological activity of COE-PIGS was demonstrated by binding to C1q component of the complement system, as well as the surface of antigen-presenting cells (APCs) in vitro. The recombinant COE-PIGS induced humoral and cellular immune responses specific for PEDV after both systemic and mucosal vaccination. Altogether, the data indicated that PEDV antigen fusion to poly-Fc could be a promising vaccine platform against respiratory PEDV infection.