Production of fluorescent antibody-labeling proteins in plants using a viral vector and the application in the detection of Acidovorax citrulli and Bamboo mosaic virus

Affinity Sedimentation and Magnetic Separation With Plant-Made Immunosorbent Nanoparticles for Therapeutic Protein Purification

The virus-based immunosorbent nanoparticle is a nascent technology being developed to serve as a simple and efficacious agent in biosensing and therapeutic antibody purification. There has been particular emphasis on the use of plant virions as immunosorbent nanoparticle chassis for their diverse morphologies and accessible, high yield manufacturing via plant cultivation. To date, studies in this area have focused on proof-of-concept immunosorbent functionality in biosensing and purification contexts. Here we consolidate a previously reported pro-vector system into a single Agrobacterium tumefaciens vector to investigate and expand the utility of virus-based immunosorbent nanoparticle technology for therapeutic protein purification. We demonstrate the use of this technology for Fc-fusion protein purification, characterize key nanomaterial properties including binding capacity, stability, reusability, and particle integrity, and present an optimized processing scheme with reduced complexity and increased purity. Furthermore, we present a coupling of virus-based immunosorbent nanoparticles with magnetic particles as a strategy to overcome limitations of the immunosorbent nanoparticle sedimentation-based affinity capture methodology. We report magnetic separation results which exceed the binding capacity reported for current industry standards by an order of magnitude.

Plant Viral Disease Detection: From Molecular Diagnosis to Optical Sensing Technology—A Multidisciplinary Review

Plant viral diseases result in productivity and economic losses to agriculture, necessitating accurate detection for effective control. Lab-based molecular testing is the gold standard for providing reliable and accurate diagnostics; however, these tests are expensive, time-consuming, and labour-intensive, especially at the field-scale with a large number of samples. Recent advances in optical remote sensing offer tremendous potential for non-destructive diagnostics of plant viral diseases at large spatial scales. This review provides an overview of traditional diagnostic methods followed by a comprehensive description of optical sensing technology, including camera systems, platforms, and spectral data analysis to detect plant viral diseases. The paper is organized along six multidisciplinary sections: (1) Impact of plant viral disease on plant physiology and consequent phenotypic changes, (2) direct diagnostic methods, (3) traditional indirect detection methods, (4) optical sensing technologies, (5) data processing techniques and modelling for disease detection, and (6) comparison of the costs. Finally, the current challenges and novel ideas of optical sensing for detecting plant viruses are discussed.

Functionalizing silica sol-gel with entrapped plant virus-based immunosorbent nanoparticles

Advancements in understanding and engineering of virus-based nanomaterials (VBNs) for biomedical applications motivate a need to explore the interfaces between VBNs and other biomedically-relevant chemistries and materials. While several strategies have been used to investigate some of these interfaces with promising initial results, including VBN-containing slow-release implants and VBN-activated bioceramic bone scaffolds, there remains a need to establish VBN-immobilized three dimensional materials that exhibit improved stability and diffusion characteristics for biosensing and other analyte-capture applications. Silica sol–gel chemistries have been researched for biomedical applications over several decades and are well understood; various cellular organisms and biomolecules (e.g., bacteria, algae, enzymes) have been immobilized in silica sol-gels to improve viability, activity, and form factor (i.e., ease of use). Here we present the immobilization of an antibody-binding VBN in silica sol–gel by pore confinement. We have shown that the resulting system is sufficiently diffuse to allow antibodies to migrate in and out of the matrix. We also show that the immobilized VBN is capable of antibody binding and elution functionality under different buffer conditions for multiple use cycles. The promising results of the VBN and silica sol–gel interface indicate a general applicability for VBN-based bioseparations and biosensing applications.

Development and optimization of a pepino mosaic virus-based vector for rapid expression of heterologous proteins in plants

Plant-virus-derived vectors are versatile tools with multiple applications in agricultural and medical biotechnology. In this study, we developed pepino mosaic virus (PepMV) (family Alphaflexiviridae; genus Potexvirus) into a vector for heterologous protein expression in plants. PepMV was initially cloned in a step-wise manner, fully sequenced and the full-length infectious clone was tested for infectivity in Nicotiana benthamiana. Initial infectious clones resulted in poor replication of PepMV and lack of systemic movement. Mutations in the viral sequence affected systemic infection. Two suspected mutations were altered to restore systemic infectivity. PepMV infection was apparent as early as 4 days post agroinfiltration (dpa) inoculation in N. benthamiana. A multiple cloning site was inserted into the PepMV genome for introduction and expression of foreign genes. Several modifications to the wild-type vector were made, such as a replacing the native subgenomic promoter (SGP) with a heterologous SGP, and introduction of translational enhancers and terminators, to improve heterologous expression of the foreign gene-of-interest. GFP was used as a reporter for monitoring virus infection and protein production. Strong GFP expression was observed as early as 4 dpa with a translational enhancer. The PepMV-based vector produces rapid expression of the foreign gene in comparison to two other potexvirus-based vectors. GFP production was monitored over time and optimal protein production was recorded between 5 and 7 dpa. GFP protein levels reached up to 4% and decreased to 0.5% total soluble protein at 7 and 14 dpa, respectively. Future studies will evaluate this virus-based vector for large-scale production of pharmaceutical compounds. KEY POINTS: • A pepino mosaic virus isolate was developed into a plant-based expression vector. • Expression levels of the heterologous protein were comparable or exceeded previously developed viral vectors. • Protein levels in plants were highest between 5 and 7 days and decreased gradually.

Production of Human IFNγ Protein in Nicotiana benthamiana Plant through an Enhanced Expression System Based on Bamboo mosaic Virus

Plant-based systems are safe alternatives to the current platforms for the production of biologically active therapeutic proteins. However, plant-based expression systems face certain major challenges, including the relatively low productivity and the generation of target proteins in biologically active forms. The use of plant virus-based expression systems has been shown to enhance yields, but further improvement is still required to lower the production cost. In this study, various strategies were employed to increase the yields of an important therapeutic protein, human interferon gamma (IFNγ), in Nicotiana benthamiana through modifications of expression vectors based on potexviruses. Among these, the vector based on a coat protein (CP)-deficient Bamboo mosaic virus (BaMV), pKB△CHis, was shown to exhibit the highest expression level for the unmodified IFNγ. Truncation of the N-terminal signal peptide of IFN (designated mIFNγ) resulted in a nearly seven-fold increase in yield. Co-expression of a silencing suppressor protein by replacing the coding sequence of BaMV movement protein with that of P19 led to a 40% increase in mIFNγ accumulation. The fusion of endoplasmic reticulum (ER) retention signal with mIFNγ significantly enhanced the accumulation ratio of biologically active dimeric mIFNγ to 87% relative to the non-active monomeric form. The construct pKB19mIFNγER, employing the combination of all the above enhancement strategies, gave the highest level of protein accumulation, up to 119 ± 0.8 μg/g fresh weight, accounting for 2.5% of total soluble protein (TSP) content. These findings advocate the application of the modified BaMV-based vector as a platform for high-level expression of therapeutic protein in N. benthamiana.

Development of Molecular Markers for Detection of Acidovorax citrulli Strains Causing Bacterial Fruit Blotch Disease in Melon

Acidovorax citrulli (A. citrulli) strains cause bacterial fruit blotch (BFB) in cucurbit crops and affect melon significantly. Numerous strains of the bacterium have been isolated from melon hosts globally. Strains that are aggressively virulent towards melon and diagnostic markers for detecting such strains are yet to be identified. Using a cross-inoculation assay, we demonstrated that two Korean strains of A. citrulli, NIHHS15-280 and KACC18782, are highly virulent towards melon but avirulent/mildly virulent to the other cucurbit crops. The whole genomes of three A. citrulli strains isolated from melon and three from watermelon were aligned, allowing the design of three primer sets (AcM13, AcM380, and AcM797) that are specific to melon host strains, from three pathogenesis-related genes. These primers successfully detected the target strain NIHHS15-280 in polymerase chain reaction (PCR) assays from a very low concentration of bacterial gDNA. They were also effective in detecting the target strains from artificially infected leaf, fruit, and seed washing suspensions, without requiring the extraction of bacterial DNA. This is the first report of PCR-based markers that offer reliable, sensitive, and rapid detection of strains of A. citrulli causing BFB in melon. These markers may also be useful in early disease detection in the field samples, in seed health tests, and for international quarantine purposes.

Potential serum biomarkers for the prediction of the efficacy of escitalopram for treating depression

BACKGROUND

Although several pharmacological treatment options for depression are currently available, a large proportion of patients still do not achieve a complete remission or respond adequately to the initial antidepressant prescribed for reasons that remain relatively unknown. This study explored the application of serum biomarkers to the predict the efficacy of escitalopram for treating depression, to guide clinical drug selection.

METHOD

In this study, 306 patients suffering from depression were treated with escitalopram (10 mg) for 6 weeks. After 6 weeks of treatment, the patients were divided into an escitalopram-sensitive group (ES, n = 172) and an escitalopram-insensitive group (EIS, n = 134) according their HAMD-24 scores after 6 weeks of treatment. Serum samples from all participants were collected on the first day, and 10 different serum biomarkers were analysed. Data from 100 patients in the ES group and 100 patients in the EIS group were then used to build a logistic regression model, and a receiver operating characteristic (ROC) curve was drawn. To validate the accuracy of our model, another 72 patients in the ES group and 34 patients in the EIS group were studied.

RESULTS

Of the 10 selected serum biomarkers, 4 were screened to build the regression model. BDNF, FGF-2, TNF-α and 5-HT. The regression equation was Z = 1/[1 + e^{-(-5.065+0.145 (BDNF)+0.029 (FGF-2)-0.368 (TNF-α)+0.813 (5-HT))}], and the 4 biomarkers-combined detection achieved an AUC (area under the ROC curve) of 0.929 and a predictive accuracy of 88.70%.

LIMITATION

Decision support tools based on our combined biomarker prediction models hold comparatively great promises; however, they need to be validated on a much larger scales than current studies provide.

CONCLUSION

The logistic regression model and ROC curves based of the serum biomarkers used in this study provide a more reliable means to predict the efficacy of escitalopram in patients with depression, and provide clinical evidence for drug selection.