Construction and expression of a synthetic gene encoding nonstructural glycoprotein NS1 of dengue 2 virus in  Pichia pastoris

Puspasari, Fernita; Putri, Riski Dwimalida; Aisyah, .; Damayanti, Raden Roro Rika; Yuwita, Anita; Alisjahbana, Bachti; Handali, Sukwan; Ihsanawati,; Natalia, Dessy

doi:10.1016/j.apjtb.2017.07.017

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…Various recombinant proteins produced using microbes and higher organisms are used as a therapeutic agents and vaccine candidates ( 12 – 14 ). The expression host system mostly used for recombinant dengue virus proteins include bacteria ( 15 ), yeast ( 16 ), mammalian cells ( 17 ), insect cells ( 18 ), transgenic animals ( 19 ), and transgenic plants ( 20 ). The recombinant proteins are mainly produced with the help of genetic engineering techniques.…”

Section: Introductionmentioning

confidence: 99%

Recent Developments in Recombinant Protein–Based Dengue Vaccines

Tripathi

Shrivastava

2018

Front. Immunol.

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Recombinant proteins are gaining enormous importance these days due to their wide application as biopharmaceutical products and proven safety record. Various recombinant proteins of therapeutic and prophylactic importance have been successfully produced in microbial and higher expression host systems. Since there is no specific antiviral therapy available against dengue, the prevention by vaccination is the mainstay in reducing the disease burden. Therefore, efficacious vaccines are needed to control the spread of dengue worldwide. Dengue is an emerging viral disease caused by any of dengue virus 1–4 serotypes that affects the human population around the globe. Dengue virus is a single stranded RNA virus encoding three structural proteins (capsid protein, pre-membrane protein, and envelope protein) and seven non-structural proteins (NS1, NS2a, NS2b, NS3, NS4a, NS4b, NS5). As the only licensed dengue vaccine (Dengvaxia) is unable to confer balanced protection against all the serotypes, therefore various approaches for development of dengue vaccines including tetravalent live attenuated, inactivated, plasmid DNA, virus-vectored, virus-like particles, and recombinant subunit vaccines are being explored. These candidates are at different stages of vaccine development and have their own merits and demerits. The promising subunit vaccines are mainly based on envelope or its domain and non-structural proteins of dengue virus. These proteins have been produced in different hosts and are being investigated for development of a successful dengue vaccine. Novel immunogens have been designed employing various strategies like protein engineering and fusion of antigen with various immunostimulatory motif to work as self-adjuvant. Moreover, recombinant proteins can be formulated with novel adjuvants to enhance the immunogenicity and thus conferring better protection to the vaccinees. With the advent of newer and safer host systems, these recombinant proteins can be produced in a cost effective manner at large scale for vaccine studies. In this review, we summarize recent developments in recombinant protein based dengue vaccines that could lead to a good number of efficacious vaccine candidates for future human use and ultimately alternative dengue vaccine candidates.

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Section: Introductionmentioning

confidence: 99%

Recent Developments in Recombinant Protein–Based Dengue Vaccines

Tripathi

Shrivastava

2018

Front. Immunol.

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“…NS1 is secreted into blood circulation in a few days after infection and can achieve high circulating level (≥600 ng/mL) within 72 h of illness (Libraty et al, 2002), making this protein a potential biomarker for early dengue infection detection. Among all four dengue serotypes (DENV-1, DENV-2, DENV-3 and DENV-4), DENV-2 was frequently associated with most severe cases and epidemics (Soo et al, 2016;Yung et al, 2015;Vicente et al, 2016) Expression of DENV-2 NS1 from different origins has been reported in various host cells ranging from prokaryotic cells, such as E. coli BL21 (DE3) (Yohan et al, 2017) and E. coli Rosetta (DE3) (Lemos et al, 2013), to eukaryotic cells, such as Pichia pastoris X-33 (Zhou et al, 2006), P. pastoris KM71 (Puspasari et al, 2017) and insect cells (Rozen-Gagnon et al, 2012). All of the recombinant proteins, however, had a different solubility depends on the host cells in which it was expressed.…”

Section: Introductionmentioning

confidence: 99%

Production of Immunologically Active Untagged Recombinant DENV-2 NS1 in Escherichia coli

Natalia

Heryakusuma

Puspasari

et al. 2018

American Journal of Biochemistry and Biotechnology

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Dengue is an infectious disease affecting 390 millions people in tropical and subtropical region annually. Dengue virus NS1 protein plays an important role in viral replication in the host cell and it is detected in high level in the infected patient serum. A synthetic gene of untagged DENV-2 NS1 with codons optimization for expression in Escherichia coli has been generated and then inserted into an expression vector pET16b. As a hydrophobic protein with aliphatic index of 71.21%, DENV-2 NS1 was produced as inclusion bodies in E. coli BL21(DE3). The DENV-2 NS1 aggregate was unfolded in 8 M urea and then refolded by reverse dilution method. The refolded DENV-2 NS1 has immunologically active structure as it is capable to interact with anti-NS1 antibody, hence making it as a potential vaccine candidate.

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Machine learning-based prediction of insufficient contrast enhancement in coronary computed tomography angiography

et al. 2022

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Objectives Patient-tailored contrast delivery protocols strongly reduce the total iodine load and in general improve image quality in CT coronary angiography (CTCA). We aim to use machine learning to predict cases with insufficient contrast enhancement and to identify parameters with the highest predictive value. Methods Machine learning models were developed using data from 1,447 CTs. We included patient features, imaging settings, and test bolus features. The models were trained to predict CTCA images with a mean attenuation value in the ascending aorta below 400 HU. The accuracy was assessed by the area under the receiver operating characteristic (AUROC) and precision-recall curves (AUPRC). Shapley Additive exPlanations was used to assess the impact of features on the prediction of insufficient contrast enhancement. Results A total of 399 out of 1,447 scans revealed attenuation values in the ascending aorta below 400 HU. The best model trained using only patient features and CT settings achieved an AUROC of 0.78 (95% CI: 0.73–0.83) and AUPRC of 0.65 (95% CI: 0.58–0.71). With the inclusion of the test bolus features, it achieved an AUROC of 0.84 (95% CI: 0.81–0.87), an AUPRC of 0.71 (95% CI: 0.66–0.76), and a sensitivity of 0.66 and specificity of 0.88. The test bolus’ peak height was the feature that impacted low attenuation prediction most. Conclusion Prediction of insufficient contrast enhancement in CT coronary angiography scans can be achieved using machine learning models. Our experiments suggest that test bolus features are strongly predictive of low attenuation values and can be used to further improve patient-specific contrast delivery protocols. Key Points • Prediction of insufficient contrast enhancement in CT coronary angiography scans can be achieved using machine learning models. • The peak height of the test bolus curve is the most impacting feature for the best performing model.

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Construction and expression of a synthetic gene encoding nonstructural glycoprotein NS1 of dengue 2 virus in Pichia pastoris

Cited by 3 publications

References 12 publications

Recent Developments in Recombinant Protein–Based Dengue Vaccines

Recent Developments in Recombinant Protein–Based Dengue Vaccines

Production of Immunologically Active Untagged Recombinant DENV-2 NS1 in Escherichia coli

Machine learning-based prediction of insufficient contrast enhancement in coronary computed tomography angiography

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