Optimizing a Multi-Component Intranasal Entamoeba Histolytica Vaccine Formulation Using a Design of Experiments Strategy

Amebiasis is a neglected tropical disease caused by Entamoeba histolytica. Although the disease burden varies geographically, amebiasis is estimated to account for some 55,000 deaths and millions of infections globally per year. Children and travelers are among the groups with the greatest risk of infection. There are currently no licensed vaccines for prevention of amebiasis, although key immune correlates for protection have been proposed from observational studies in humans. We previously described the development of a liposomal adjuvant formulation containing two synthetic TLR ligands (GLA and 3M-052) that enhanced antigen-specific fecal IgA, serum IgG2a, a mixed IFNγ and IL-17A cytokine profile from splenocytes, and protective efficacy following intranasal administration with the LecA antigen. By applying a statistical design of experiments (DOE) and desirability function approach, we now describe the optimization of the dose of each vaccine formulation component (LecA, GLA, 3M-052, and liposome) as well as the excipient composition (acyl chain length and saturation; PEGylated lipid:phospholipid ratio; and presence of antioxidant, tonicity, or viscosity agents) to maximize desired immunogenicity characteristics while maintaining physicochemical stability. This DOE/desirability index approach led to the identification of a lead candidate composition that demonstrated immune response durability and protective efficacy in the mouse model, as well as an assessment of the impact of each active vaccine formulation component on protection. Thus, we demonstrate that both GLA and 3M-052 are required for statistically significant protective efficacy. We also show that immunogenicity and efficacy results differ in female vs male mice, and the differences appear to be at least partly associated with adjuvant formulation composition.

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Applying Statistical Design of Experiments To Understanding the Effect of Growth Medium Components on Cupriavidus necator H16 Growth

Applied and Environmental Microbiology ◽

10.1128/aem.00705-20 ◽

2020 ◽

Vol 86 (17) ◽

Cited By ~ 1

Author(s):

Christopher C. Azubuike ◽

Martin G. Edwards ◽

Angharad M. R. Gatehouse ◽

Thomas P. Howard

Keyword(s):

Amino Acids ◽

Design Of Experiments ◽

Cell Density ◽

Growth Medium ◽

Statistical Design ◽

Statistical Design Of Experiments ◽

Content Type ◽

Medium Components ◽

Defined Media ◽

The Impact

ABSTRACT Cupriavidus necator H16 is gaining significant attention as a microbial chassis for range of biotechnological applications. While the bacterium is a major producer of bioplastics, its lithoautotrophic and versatile metabolic capabilities make the bacterium a promising microbial chassis for biofuels and chemicals using renewable resources. It remains necessary to develop appropriate experimental resources to permit controlled bioengineering and system optimization of this microbe. In this study, we employed statistical design of experiments to gain understanding of the impact of components of defined media on C. necator growth and built a model that can predict the bacterium’s cell density based on medium components. This highlighted medium components, and interaction between components, having the most effect on growth: fructose, amino acids, trace elements, CaCl2, and Na2HPO4 contributed significantly to growth (t values of <−1.65 or >1.65); copper and histidine were found to interact and must be balanced for robust growth. Our model was experimentally validated and found to correlate well (r2 = 0.85). Model validation at large culture scales showed correlations between our model-predicted growth ranks and experimentally determined ranks at 100 ml in shake flasks (ρ = 0.87) and 1 liter in a bioreactor (ρ = 0.90). Our approach provides valuable and quantifiable insights on the impact of medium components on cell growth and can be applied to model other C. necator responses that are crucial for its deployment as a microbial chassis. This approach can be extended to other nonmodel microbes of medical and industrial biotechnological importance. IMPORTANCE Chemically defined media (CDM) for cultivation of C. necator vary in components and compositions. This lack of consensus makes it difficult to optimize new processes for the bacterium. This study employed statistical design of experiments (DOE) to understand how basic components of defined media affect C. necator growth. Our growth model predicts that C. necator can be cultivated to high cell density with components held at low concentrations, arguing that CDM for large-scale cultivation of the bacterium for industrial purposes will be economically competitive. Although existing CDM for the bacterium are without amino acids, addition of a few amino acids to growth medium shortened lag phase of growth. The interactions highlighted by our growth model show how factors can interact with each other during a process to positively or negatively affect process output. This approach is efficient, relying on few well-structured experimental runs to gain maximum information on a biological process, growth.

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Student engagement with statistical design of experiments by active learning projects

Proceedings of the 2nd International Conference on Higher Education Advances ◽

10.4995/head16.2016.2650 ◽

2016 ◽

Cited By ~ 2

Author(s):

Isabel M Joao ◽

Joao M Silva

Keyword(s):

Active Learning ◽

Learning Environment ◽

Design Of Experiments ◽

Statistical Design ◽

Education Institution ◽

Fractional Factorial ◽

Factorial Designs ◽

Fractional Factorial Designs ◽

Statistical Design Of Experiments ◽

The Impact

This paper illustrates the use of design of experiments in an active learning environment in a new Master course in Quality and Environmental Engineering at a higher education institution in Portugal. The study took place in the unit of Advanced Techniques for Quality. The aim of this work is to explain how in an active learning environment the students worked on projects designed to use fractional factorial designs in order to improve a system including the impact that the approach had on students. Twelve master students took part of the classroom projects. Three groups of students worked on projects, created and developed by them contributing to increase their commitment and enthusiasm. In a classroom session the students made a presentation and the results were discussed. Each group also produced a video with the planning and execution of the fractional factorial designs which was helpful to start the debate. The active learning approach required that the students developed their own projects and decide when and how to do the experiments. Taking the responsibility of their activities was very enriching forcing the students to think about the things they did and questioning some of their own decisions.

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