Introduction

To approach process design efficiently, we started by looking at the monumental efforts of our predecessors¹. Due to similarities in reaction conditions, we took green chemical production methods as a reference point for our process design. Namely, the synthesis of nanoparticles with ascorbic acid, as outlined by Cheng et al. ² was deemed the most representative of our aspirations. The authors obtained star-shaped nanoparticles with a plasmon peak^info at 800 nm. This fits almost all our prerequisites (read more about this on the Project Description page), as these properties are optimal for use in photothermal therapy (PTT). However, this methodology does not yield bimetallic nanoparticles. We aimed to make this possible with our biomanufacturing process by using this synthesis methodology as the starting point for our process design.

Cycle 1. Determining the optimal HAuCl₄:AgNO₃ ratio for PTT-optimized nanoparticles production with ascorbic acid

Design

First, we decided to identify the optimal conditions for chemical nanoparticle synthesis using ascorbic acid. This way we could investigate several parameters in a more simple setting before moving on to a complex biological system. Additionally, to bridge the gap between chemical and biological synthesis, the reduction with ascorbic acid was conducted at pH 7 instead of pH 3, as done in the reference paper². This was done under the presumption that optimal functionality of reducing enzymes present in Escherichia coli (E.coli) is achieved at neutral pH, as it corresponds to the pH of optimal growth in this bacterium⁶. As this methodology deviates from the original paper, the ascorbic acid experiments were repeated at biologically relevant pH to obtain an optimal gold:silver (HAuCl₄:AgNO₃) ratio for this pH range.

We used Box-Behnken Design to minimize the number of experiments necessary to identify the optimal HAuCl₄:AgNO₃ ratio for the synthesis of nanoparticles with a plasmon peak at 800 nm. For a more detailed description of Box-Behnken Design, you can refer to the Modeling page. We could find the optimum for three variables in just 15 experiments instead of 27. The three variables were (1) the concentration of AgNO₃ (2) the concentration of HAuCl₄, and (3) pH. The latter was varied between 5 and 9 to test the influence of pH on the formation of nanoparticles under biologically relevant pH conditions⁶.

Build & Test

After synthesis, the 450-1000 nm absorption spectrum was measured for each sample. These spectra were used as input for the model, which then returned a correlation between the three variables and the absorbance, displayed as an interactive slider in Fig. 3. This yielded a prediction of the spectrum, while the main optimization objective was a high absorbance at 800 nm. You can refer to the Modeling page for a detailed discussion of the methodology and the results of this experiment.

Learn

The model predicted an optimal molar ratio of HAuCl₄:AgNO₃ = 1.80:1 at a pH of 6.1. However, as will be elaborated in Cycle 2, Mueller Hinton (MH) Broth was shown to be an optimal growth medium for nanoparticle production. The pH of MH Broth is 7.3, thus the model was adjusted to maximize A_{800 nm} for this pH value. This yielded a ratio of 1.85:1. Subsequently, the spiky morphology of the prepared nanoparticles was confirmed using TEM (Fig. 4). This “golden ratio” was used for all subsequent experiments with the biological system, because the produced nanoparticles in this experiment had the correct shape and size to observe plasmon resonance at 800 nm.

Cycle 2. Getting the right biological system for nanoparticle production

Design

The next step in developing the biomanufacturing system was establishing which growth medium allows the model organism E. coli BL21 to produce the most effective blend of reducing agents. Extensive literature reviews show that the reducing agents play a crucial role in the size and morphology of the produced nanoparticles ⁴, which demands fine-tuning the bioreducing system.

Gurunathan et al.⁸ has shown the capacity of E. coli supernatant to produce silver nanoparticles from AgNO₃ within five minutes⁷. The supernatant was obtained after 24h of growth in MH broth. After unsuccessfully attempting this conveniently short synthesis method, another paper stating that nanoparticle synthesis occurred in 24h was consulted⁸. Preliminary tests showed that this timespan was indeed sufficient. Therefore, after this point, all biochemical synthesis was performed over 24h.

To assess the optimal media for bacterial growth, we performed nanoparticle synthesis with supernatants of four different media: LB, LB Low Salt, MH, TSBS. Another variable tested was whether it is better to lyse the cells used for nanoparticle production. Lysing of the cells can be achieved by sonicating the cell liquid culture before separating the supernatant from the pellet. The Results page further discusses the choice of media and sonication settings.

Build & Test

The optimal medium for nanoparticle production was chosen based on the best absorbance at 800 nm and further confirmed with Transmission Electron Microscopy (TEM). An overview of the main findings is presented below, see the bar plots with A_{800 nm} of different media (Fig. 5) and TEM micrographs (Fig. 6). A complete description of our results can be found on the Results page.

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MH supernatant without the lysate was found to have the best capacity for producing nanoparticles with the desired morphology (see Fig. 6 for spiky spheres) and a plasmon peak at 800 nm. Therefore, this engineering cycle helped us establish another parameter for Binanox: the optimal medium for bacterial growth of nanoparticle-producing E. coli.

It was also noticed that the control samples with media, silver, and gold salts could also produce nanoparticles. Therefore, to test which constituents of the media were responsible for the reducing capacity, another experiment was set up, as described on the Results page.

Cycle 3. Boost Binanox with synthetic biology

After establishing the optimal medium and treatment of the biological system for nanoparticle production, we proceeded to the next step: further improving the biomanufacturing of nanoparticles by adding specific metal-reducing proteins. As seen in the literature, Cupriavidus metallidurans proteins CopA ^{9, 10} and NapA ^{11, 12, 13} have been studied in nanoparticle synthesis. In addition, the cup1 gene from Candida albicans was also shown to improve nanoparticle synthesis¹⁴. The beneficial effect of these proteins is mainly achieved through the increase in the reduction capacity of the mix. This typically leads to a higher yield and can influence the morphology⁴.

Design

To test the effect of the selected genes on nanoparticle production, we isolated the ASKA pCA24N plasmids from the library-standard E. coli K12 and cloned them into our E. coli BL21 strain. This allowed us to overexpress these genes. The proteins were all expressed intracellularly, so after IPTG induction, the pellet of a liquid culture would contain a high concentration of the protein of interest. After this, the pellet was resuspended in a smaller volume and lysed through sonication. Finally, this pellet lysate containing the overexpressed protein of interest was added to the MH supernatant of E. coli BL21 with an empty pET16b plasmid (introduced for antibiotic resistance). We then added silver and gold salts to this reaction mix to study nanoparticle formation.

The expected effect of all proteins on nanoparticle synthesis was a higher yield due to an increase in the reduction capacity of the mix. However, a change in the reaction mix can lead to changes in the synthesized nanoparticles' morphology, size distribution, and composition⁴. In this cycle, we directed our attention to the yield of nanoparticles with an absorbance at 800 nm, expressed in the intensity of A_{800 nm}. Such an inference could be made after a supplementary experiment that found a direct correlation between nanoparticle concentration and absorbance (for more information, see the Results page).

Build & Test

Upon confirmation of the IPTG-induced overexpression of the proteins (see Results page for SDS gel), nanoparticle synthesis was performed according to the methodology described above. Additionally, when MelA was used for synthesis, L-DOPA was added, as MelA converts L-DOPA into the reducing agent melanin. Finally, absorption spectra were measured and compared to the controls without adding the proteins (Fig. 7).

A comparison was held between wildtype (control) and samples that contained the overexpressed proteins. Error bars represent standard error (n = 3). See Results page for full spectra, including those of control samples.

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All the tested ASKA genes showed a significant decrease in A_{800 nm} when added to MH (p < 0.05). By contrast, when added to WT E. coli BL21 supernatant, no significant difference (p > 0.20) was observed compared to the control. Moreover, most samples leaned towards a decrease in A_{800 nm}, except for MelA with L-DOPA. MelA-containing lysate resulted in a significant increase for A_{800 nm} compared to its control (p < 0.0005), which contained a lysate of WT. However, this increase was insignificant compared to the control without any lysate (p = 0.317). Observing that the absorbance becomes lower upon the addition of lysate is peculiar.

A potential clarification for this decline in nanoparticle producing capacity is the interaction of the overexpressed proteins with other compounds in the reducing mix, which causes the overall mix to be less effective in synthesizing nanoparticles. Such compounds could be other oxidizing agents that compete with metal ions. Alternatively, proteases could be disturbing the functionality of the reducing peptides. Both scenarios lead to a decrease in nanoparticle yield, as the reduction of metal ions experiences a significant drop. A more elaborate discussion of this prospect is discussed on the Results page. In addition, the integration of these results into Binanox is discussed in Cycle 4.

Cycle 4. Further improving the Binanox system with nitrate-containing media

The last step we undertook to optimize our biomanufacturing process was ensuring a better reducing power of the supernatant, to which we added the lysate with overexpressed proteins. According to a paper by Gurunathan et al.⁸, the presence of nitrate in the medium during growth increases the reducing capacity of the supernatant due to an increase in nitrate reductase production by the organism⁸. In addition, nitrate reductases, such as NapA, are responsible for silver nanoparticle synthesis¹⁷. Following this train of thought, we decided to test whether adding nitrate to MH would improve the yield of nanoparticle production by the supernatant-lysate mix.