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整合纳米颗粒定量分析和实验统计学设计,以提高 High Five 细胞中 HIV-1 病毒样颗粒的产量。

Integrating nanoparticle quantification and statistical design of experiments for efficient HIV-1 virus-like particle production in High Five cells.

机构信息

Departament d'Enginyeria Química, Biològica i Ambiental, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona, Spain.

IQS School of Engineering, Universitat Ramón Llull, Barcelona, Spain.

出版信息

Appl Microbiol Biotechnol. 2020 Feb;104(4):1569-1582. doi: 10.1007/s00253-019-10319-x. Epub 2020 Jan 6.

DOI:10.1007/s00253-019-10319-x
PMID:31907573
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7224031/
Abstract

The nature of enveloped virus-like particles (VLPs) has triggered high interest in their application to different research fields, including vaccine development. The baculovirus expression vector system (BEVS) has been used as an efficient platform for obtaining large amounts of these complex nanoparticles. To date, most of the studies dealing with VLP production by recombinant baculovirus infection utilize indirect detection or quantification techniques that hinder the appropriate characterization of the process and product. Here, we propose the application of cutting-edge quantification methodologies in combination with advanced statistical designs to exploit the full potential of the High Five/BEVS as a platform to produce HIV-1 Gag VLPs. The synergies between CCI, MOI, and TOH were studied using a response surface methodology approach on four different response functions: baculovirus infection, VLP production, VLP assembly, and VLP productivity. TOH and MOI proved to be the major influencing factors in contrast with previous reported data. Interestingly, a remarkable competition between Gag VLP production and non-assembled Gag was detected. Also, the use of nanoparticle tracking analysis and flow virometry revealed the existence of remarkable quantities of extracellular vesicles. The different responses of the study were combined to determine two global optimum conditions, one aiming to maximize the VLP titer (quantity) and the second aiming to find a compromise between VLP yield and the ratio of assembled VLPs (quality). This study provides a valuable approach to optimize VLP production and demonstrates that the High Five/BEVS can support mass production of Gag VLPs and potentially other complex nanoparticles.

摘要

包膜病毒样颗粒 (VLPs) 的性质引发了人们对其在不同研究领域应用的浓厚兴趣,包括疫苗开发。杆状病毒表达载体系统 (BEVS) 已被用作获得大量这些复杂纳米颗粒的有效平台。迄今为止,大多数涉及重组杆状病毒感染生产 VLP 的研究都利用间接检测或定量技术,这些技术阻碍了对该过程和产品的适当表征。在这里,我们提出应用最先进的定量方法结合先进的统计设计,以充分利用 High Five/BEVS 作为生产 HIV-1 Gag VLP 的平台的潜力。通过响应面方法学方法,在四个不同的响应函数上研究了 CCI、MOI 和 TOH 的协同作用:杆状病毒感染、VLP 生产、VLP 组装和 VLP 生产力。与以前报道的数据相比,TOH 和 MOI 被证明是主要的影响因素。有趣的是,检测到 Gag VLP 生产和未组装的 Gag 之间存在显著的竞争。此外,使用纳米颗粒跟踪分析和流式病毒计量法揭示了存在大量细胞外囊泡。将研究中的不同响应结合起来确定了两个全局最优条件,一个旨在最大限度地提高 VLP 滴度(数量),另一个旨在在 VLP 产量和组装的 VLP 比例(质量)之间找到折衷。本研究提供了一种优化 VLP 生产的有价值的方法,并表明 High Five/BEVS 可以支持大量生产 Gag VLP 和潜在的其他复杂纳米颗粒。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4d9/7224031/756cbea57eba/253_2019_10319_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4d9/7224031/56335e92e0f9/253_2019_10319_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4d9/7224031/129b4406942b/253_2019_10319_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4d9/7224031/16c3859c965d/253_2019_10319_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4d9/7224031/f665831e237d/253_2019_10319_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4d9/7224031/4ae9a666c684/253_2019_10319_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4d9/7224031/756cbea57eba/253_2019_10319_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4d9/7224031/56335e92e0f9/253_2019_10319_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4d9/7224031/129b4406942b/253_2019_10319_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4d9/7224031/16c3859c965d/253_2019_10319_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4d9/7224031/f665831e237d/253_2019_10319_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4d9/7224031/4ae9a666c684/253_2019_10319_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4d9/7224031/756cbea57eba/253_2019_10319_Fig6_HTML.jpg

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