PROJECT | EXPANDED NANO CAGES: UWRAPPING NANO BLACK BOXES

Issue | Approach


ISSUE

The concept of expansion is highly related to development of new ideas that make colossal advances possible. Our project is all about that: rationalize a biological molecular system to design a prototype to optimize biochemical reactions. This prototype is an auto-organized DNA structure designed to be used as a "black box", accepting as input a substrate molecule and giving as output a desired biomolecule as product. The principal issue approached is how would be a bioindustrial productive process with those boxes and what are the key elements for designing those processes.

 

The Black Boxes Inspiration

Black boxes could be seen both as layers on a abstract hierarchy of information or as modules of a device or a process1. Those abstractions and modularization are strategies mainly used on electrical and computer engineering, and are focused on how to control the flow of information and interaction between elements of the whole system. They are useful for flexibilizing the development of the system's components, ease the problem solving process2 and in ultimate instance make the use of the system more friendly3.

Let's take for instance the computer you are reading this text: you are on the top of the abstraction layers hierarchy, on the operational system with all its virtual buttons and windows. Under this layer is the code that is being executed to give what you're seeing, under it is the kernel and under the kernel is many other layers that end on the electronic dispositives, part of the hardware of you computer (Fig 1. a). Each layer is like a "black box", this device whose inner works are hidden but its inputs and outputs are known (Fig 1. b). The usefulness of those boxes rely on the flexibility the whole system gains to do different tasks, like run different softwares and programs on your computer using the same abstraction layer architecture - the opposite would be having a different machine that is built specifically for each program you use on your computer. This is not done with the intention to segregate information, but to ease the development and use of electrical and digital systems, which complexity is always growing driven by rapid technological innovation4.

Biological System as Black Boxes

But what all this stuff has to do with biological design? Everything. The flexibility and modularization are also characteristics that belong to biological systems developed through evolution5. The biological organization is completely hierarchical, like abstractions layers, going from atoms and molecules to cells, organs, individuals and on top of that, herds (Fig 2)6. Modularization by compartmentalization is therefore another characteristic in common between those systems7, being essential for appropriate specialized biochemical reactions8. This similarity between eletro-digital systems and biology emerge mainly because both cases behave as networks, where stochastic processes of interaction between elements of the net determine the output of the system9,10.


Figure 2. Biological hierarquical design.


Engineering Nano Black Boxes

Since abstraction hierarchy by modularization is a pattern for industrial processes and biology, engineer new modules for building new synthetic biochemical systems is a natural way of development of an emergent biotech industry11. The current technology of design and construction of precise biochemical nanostructures is one of the more precise and flexible tools to achieve this objective12.

Using the technology of DNA Origami, our project proposes the design of modules of "nanocages" scaffolds that enclose biochemical pathways and optimize the overall reaction dynamics, acting almost literally as "black boxes" - because they're almost literal boxes that "hide" different inner processes. Those boxes could be in the shape of any regular polyhedra, and we present an original software that can generate in silico oligonucleotide sequences for any polyhedron with a defined volume. We prove the functionality of this software by experimentally building these nanocages and evaluate by 3D modelling the feasibility of these catalytic cages, adding features to the design for application on an industrial process. It is also shown a deterministic mathematical modelling of the system's dynamic.

Summarizing, we have 5 main objectives:

 

1. Propose a general design process for production of enzymatic DNA scaffolds using our software as a key feature for design flexibilization.

2. Show experimentally that the predictions of our software are correct for a specific polyhedra as a evidence of its functionality as a tool for designing nanocages.

3.Create 3D model examples of catalytic nanocages and support the proposed design by extensive literature review.

4. Model mathematically the dynamic of enzymatic catalysis with and without scaffold for theoretical efficiency comparison.

5. Extensively analyse the industrial challenges for implementation of DNA scaffolds for biochemical pathways optimization of catalysis.

6. Contribute to develop Brazil on innovative research about bioengineering through a more interdisciplinary and open approach for scientific innovation.

References

[1] Mills, H. D., Linger, R. C., & Hevner, A. R. (1987). Box structured information systems. IBM Systems Journal, 26(4), 395-413.

[2] Parnas, D. L. (2002). On the criteria to be used in decomposing systems into modules. In Software pioneers (pp. 411-427). Springer Berlin Heidelberg.

[3] Andrianantoandro, E., Basu, S., Karig, D. K., & Weiss, R. (2006). Synthetic biology: new engineering rules for an emerging discipline. Molecular systems biology, 2(1).

[4] Rycroft, R. W., & Kash, D. E. (1999). The complexity challenge: Technological innovation for the 21st century. Cengage Learning EMEA.

[5] Schad, E., Kalmar, L., & Tompa, P. (2013). Exon-phase symmetry and intrinsic structural disorder promote modular evolution in the human genome. Nucleic acids research.

[6] Murata, S., & Kurokawa, H. (2012). Self-organizing robots (Vol. 77). Springer.

[7] Ishii, K., & Yang, T. G. (2003, January). Modularity: international industry benchmarking and research roadmap. In ASME 2003 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (pp. 1-11). American Society of Mechanical Engineers.

[8] Chen, A. H., & Silver, P. A. (2012). Designing biological compartmentalization. Trends in cell biology, 22(12), 662-670.

[9] Barabasi, Albert-Laszlo, and Zoltan N. Oltvai. "Network biology: understanding the cell's functional organization." Nature reviews genetics 5.2 (2004): 101-113.

[10] Dorogovtsev, S. N., & Mendes, J. F. (2013). Evolution of networks: From biological nets to the Internet and WWW. Oxford University Press.

[11] Purnick, P. E., & Weiss, R. (2009). The second wave of synthetic biology: from modules to systems. Nature reviews Molecular cell biology, 10(6), 410-422.

[12] Saccà, B., & Niemeyer, C. M. (2012). DNA origami: the art of folding DNA. Angewandte Chemie International Edition, 51(1), 58-66.

 

 

APPROACH

The great issue we are addressing is how to design a molecular system that could be used as a component in a higher abstraction hierarchy on a bioproduction process. More specifically, the design concern is how to minimize the interenzyme active site distance in a generic metabolic pathway and make this solution easier to handle and implement. Here we explain and justify the approach used for the molecular design proposed on our project.

 

Enzymetic Scaffold

The job of an enzymatic scaffold is simple: hold enzymes that are involved on a reaction pathway near each other - like an industrial shed that keeps all factory machines in a same space to optimize production logistics. However, couple enzymes on macromolecular structures is not a new concept. Studies dating back 70’s, have already explored this idea using polymer matrices to hold a three enzyme system1. More recently, protein scaffolds were observed occurring naturally on eukaryotic cells as multiprotein complexes acting on cellular signaling pathways2,3. Although subsequent developments have shown that protein and RNA14 scaffolds can be feasible, functional4 and present some flexibility5, the larger control of molecular shapes provided by DNA Origami technology makes DNA an attractive option for controlling accurately the positioning and distribution of enzymes6.

In the last years, outstanding works have addressed different architectures of DNA scaffolds, like sheets7, tubes8,9 and polyhedra10. Tubular and planar designs have been reported to achieve respectively 69 and 88 fold increase on enzymatic kinetics in vitro. Even if any assay was found in literature showing kinetic data for DNA polyhedra, the encapsulation of enzymes were proved experimentally feasible10,11 and have promising design features. All those designs use similar approaches to crosslink proteins to DNA12. One of the most popular use bifunctional crosslinkers that react with thiol or amino groups from DNA or protein8,11,13, what in general requires a specific nucleotide modification at the 5' C carbon at the beginning of the oligonucleotides that compose de DNA Origami structure. There is a great range of crosslinkers commercially available with different lengths and functional groups15, making this a robust and flexible choice to develop any particular metabolic pathway, matching the objectives of our project (for more discussion about the crosslinkers proposed on our theoretical design, see Molecular Design section.

A comparison between the existent scaffold designs indicates a logic advantage for three dimensional designs (cages) in comparison with the two (planar) and one (nanotube) dimensional cases. In the review of J.L. Linn et al6 recent relevant literature about scaffolded enzymatic reactions was covered and three design rules were defined for engineering those nanostructures for catalysis enhancement:

1. Close interenzyme distance (about a few nanometers),

2. Enzyme active site correct orientation,

3. Proper scaffold multi-enzyme architecture aiding on the convenient enzyme placement (experimental claim).

Taking this into account, a polyhedral nanocage design is the best architecture to enable an optimal interenzyme distance with proper placement for the whole enzymes. This configuration creates a compartment at the same time that allows the substrates and products to getting in and out the cage, confining only the enzymes but not the solution around it - in contrast with polyhedral nanoboxes18,19,20,22. Two-dimensional scaffolds have more utilities than approximate enzymes, like channeling substrates through its surface16. This is not necessarily a constraint for scaffolding a metabolic pathway, considering that the diffusion of substrates are spherical and don't favor a specific flow of subtracts17. For a in vitro approach of enzymatic catalysis there is no need of substrate channeling, again favoring the 3D polyhedral nanocage design for scaffolding.

If the best design for in vitro catalysis enhancement using DNA scaffolds is a polyhedral nanocage, then ease and flexibilize this step of the development process of DNA scaffolding for biocatalysis is a determining part of this project's objectives. To address this we explore the functionality of a software that easily generates polyhedral nanocages, the "Polygen".

 

Design in Silico

The molecular design of this project in centered on Polygen, a program that with simple and little input could generate a myriad of DNA Origami nanocages in the shape of regular polyhedra with defined internal volume. All 3D modelling and theoretical approaches developed on the "Molecular Design" section use the structures and oligonucleotide sequences given by Polygen. The work did in lab was to show first experimental evidence that the structures specifically predicted by the software behave as expected. A truncated octahedron was chose to be constructed because its theoretical evidence on stability21,23.

In addition to Polygen software, we use three other in silico tools: the [UCSF Chimera ] for visualization and analysis of our designs, the [KEGG database ] and the [Metabolic Tinker], a big data bioinformatics online tool that help the discovery of new biochemical pathways. These softwares are part of a proposal of work process on developing generic metabolic pathways scaffolds from scratch, as discussed on Molecular Design section. Further information about how the polygen software works and its role in the context of other design softwares are described on the Dry Lab section, at Polyhedron Software Generator page .

 

Industrial Application

We believe that good process design is that one that take into account a holistic view of all the variables involved. To do so is necessary go beyond the molecular design issues related with the construction and testing the variables of catalytical scaffolds at research lab level and think on the bioindustrial production context, also evaluating the application potential on the business and productive process point of view.

Before evaluating the industrial potential, simply considering the general bioproduction process of valuable metabolites and pharmaceuticals it's clear that the molecular design could be improved. The undoubtedly most expensive processes of bioproduction are separation and purification, being responsible for 50-80% of the production costs of biopharmaceuticals and natural bioproducts24,25,27, and remain too high even with emergent options25,26. Our approach to address this issue is inspired on the recent ecological hydrometallurgy approaches28 to retrieve metal ions from aqueous solutions. This is done using nanoparticles to sequester the ions, for subsequent separation by a magnetic field application29. Same could be done for separating the catalytical nanocages on a in vitro industrial (and also research lab) scale by attaching superparamagnetic nanoparticles on its exterior, retrieving the cages for reuse while easily and cheaply collecting the solution with the bioproduct. Magnetic nanoparticles relatively are easy to synthesize and functionalize30, and also readily commercially available31,32, making this design choice very feasible. To check how we theoretically propose this, go to Molecular Design page .

Besides this practical application issue, one big question remains: is DNA nanocages bioproduction commercially feasible?

The actual pharmaceutical industry production processes for the obtention of active ingredients and its precursors are mainly based on the extraction and purification of complex molecules generated by series of reactions that occur inside living organisms such as bacteria, yeast and plants33,34. Some of these reactions are natural to the organisms where they take place and some other are bioengineered by man. Apart from the regulatory stages of creating a product by means of bioengineering, we will comment on some stages involved in bioproducts development: laboratory stage, scaling-up stage and commercial stage35. Each of these stages of development has its own challenges, efforts and general chronograms associated with. Here we highlight some aspects involved in each of these stages both for what we will call “actual/traditional process" and what we will call “nanocages biogeneration process".

During the lab stage some of the tasks traditionally needed for generating a bioproduct by bioengineering include gene and protein identification and study, strain genetic preparation, strain testing and optimization and final bench quantitative/qualitative evaluation .These processes take a long time to be done, even with the most modern techniques, since most of them are done manually with the results being analyzed manually. Another important aspect almost inherent to the lab process is the unpredictability, that can delay plans and create further complications36,37.

The process for bioproduction using DNA nanocages has several similarities and differences with the traditional process in laboratory stage. For example, instead of having to genetically modify a organism, the nanocage designer will have to project and study the dimensions and bonding specificities for the enzymes to be attached to the nanocage. An important similarity and bottleneck in bioproduction is the acquisition of all enzymes and cofactors needed for the implementation of a given natural or artificial pathway, since these enzymes must be acquired from an external supplier or be produced internally – in this case, more processes are involved, increasing complexity and potential points of failure in the overall process. We estimate that the time and cost difference between these approaches (traditional vs nanocages) in the laboratory stage do not yet pose a significant improvement in favour of the decision of one or other approach as the most effective one.

We think that both the approaches are prone and destined for optimization in the following years. Today, both of them rely heavily on manual work and on heuristics, bringing down lab performance. The manual work side of the problem is being tackled by a evident change in mindset both in industry and academia with giants like Thermo Scientific, Siemens and Becton & Dickinson dedicating whole product lines and new services focusing on lab automation. Lots of new companies are also working on bioreactor automation and control, and on integrated real time analysis, such as Sensa.io, Arcturus Biocloud, Transcriptic, Emerald Therapeutics and Zymergen.

We also see a lot of effort concerned on the heuristics problem in biotechnology and we believe the growing trend of scientific convergence will have a decisive role in the creation of better models38,39, where we know more about the system, and have more tools that we can use to predict and simulate things accurately, reducing try-and-error tactics importance in the overall process40. Convergence will/already act by providing different views from different disciplines into common problems.

One very important bottleneck for having a viable commercial process of bioproduction is achieving a good, efficient and controllable scale up between what was proved in the laboratory stage and a commercial scale production process41. A good number of projects fail or overspend during the scale up stage42. Some known issues involved in cultivating organisms that produce a certain compound are related to bacterial quorum sensing and elicitation mechanisms43,44 differences in populational density throughout bioreactor volume45, growth and survival of populations, plasmid loss during cultivation46, between others.

Since the proposed DNA nanocages biogeneration process depends purely on chemical (on opposition to biochemical) reactions, one of its theoretical advantages is not having any of the problems related above. The problems associated with the scaling up of DNA nanocage biogeneration would be more associated with chemical engineering than with bioprocess engineering47. Drawing from our mathematical modelling and from the literature, we propose that we can expect and actually find a scale up curve for a given DNA nanocage biogeneration assembly – the combination between the nanocage shape, size and combination of attached enzymes, substrate and reactants – and that this scale up curve will be enough to predict fairly well the behaviour of this bioproduction system both in low and high volume reactors.This is an interesting possibility, since the scale up process currently draw lots of resources, takes a lot of time, is riddled with problems and can generate a lot of stress in both investors and researchers48. More efforts should be concentrated on creating models and running tests that can give us more data from which we can ask more questions on (for example for providing evidence of this “orderly" behaviour of the DNA nanocage biogeneration scaling up. Most of the production work could take place on standard microreactors49, probably with enough production on microreactors to supply a commercial testing program (for example, clinical trials). There is significant evidence towards a less riskier and more controllable scale up when comparing enzyme biocatalysts - with or without nanostructure enzyme immobilization - with current bio and organic synthesis techniques.

There are no known companies working today with DNA nanocages as alternatives for bioproduction and this section is a brief speculative comment on what we think can be ways that may pave the way for the real application of DNA nanocages in production processes. An interesting aspect and possibility is the evidence towards significant higher efficiency in terms of catalytic activity inside the functionalized nanostructures, in some cases exhibiting performance improvements as high as 16-77x7,4. It means that optimally, we would need lower reactant volumes for achieving same or better yields of the wanted molecule. Most of the active ingredients are obtained by performing relatively simple chemical operations on complex molecules, requiring something from 6-15 intermediate steps to generation. Each of these steps is currently very costly environmentally, since most steps like separation, purification and crystallization require high volumes of solvents - evidentiated by an E factor (proportion kg waste/ kg product) 25-100x higher in pharmaceutical production compared to bulk chemical production50. Using enzymatic catalysis, that are known cases where 13 organic synthesis steps were substituted by one step of enzymatic catalysis51,52.

There is also a significant energy consumption reduction and a drastic reduction on solvent and reagent use53 when using enzymes as reaction catalysts. Both of this aspects are crucial to the competitiveness of a given production process. Lots of industrial processes are currently using biocatalysts, usually with very good results, with reported yields for commercialised processes typically well over 80% and mostly over 90%54. The combination between this data and the above mentioned evidence supporting high biocatalysis performance, specially on immobilized structures, indicate that the possibility of using nanostructures as hosts to “nano-factories" is very real and could be an alternative to a variety of actual production process.

 

References

[1] Mattiasson, B., & Mosbach, K. (1971). Studies on a matrix-bound three-enzyme system. Biochimica et Biophysica Acta (BBA)-Enzymology, 235(1), 253-257.

[2] Elion, E. A. (1995). Ste5: a meeting place for MAP kinases and their associates. Trends in cell biology, 5(8), 322-327.

[3] Brown, M. D., & Sacks, D. B. (2009). Protein scaffolds in MAP kinase signalling. Cellular signalling, 21(4), 462-469.

[4] Dueber, J. E., Wu, G. C., Malmirchegini, G. R., Moon, T. S., Petzold, C. J., Ullal, A. V., ... & Keasling, J. D. (2009). Synthetic protein scaffolds provide modular control over metabolic flux. Nature biotechnology, 27(8), 753-759.

[5] Skerra, A. (2000). Engineered protein scaffolds for molecular recognition. Journal of Molecular Recognition, 13(4), 167-187.

[6] Lin, J. L., Palomec, L., & Wheeldon, I. (2014). Design and Analysis of Enhanced Catalysis in Scaffolded Multienzyme Cascade Reactions. ACS Catalysis, 4(2), 505-511.

[7] Fu, J., Liu, M., Liu, Y., Woodbury, N. W., & Yan, H. (2012). Interenzyme substrate diffusion for an enzyme cascade organized on spatially addressable DNA nanostructures. Journal of the American Chemical Society, 134(12), 5516-5519.

[8] Fu, Y., Zeng, D., Chao, J., Jin, Y., Zhang, Z., Liu, H., ... & Fan, C. (2012). Single-step rapid assembly of DNA origami nanostructures for addressable nanoscale bioreactors. Journal of the American Chemical Society, 135(2), 696-702.

[9] Linko, V., Eerikäinen, M., & Kostiainen, M. A. (2015). A modular DNA origami-based enzyme cascade nanoreactor. Chemical Communications, 51(25), 5351-5354.

[10] Flory, J. D., Simmons, C. R., Lin, S., Johnson, T., Andreoni, A., Zook, J., ... & Fromme, P. (2014). Low temperature assembly of functional 3D DNA-PNA-protein complexes. Journal of the American Chemical Society, 136(23), 8283-8295.

[11] Erben, C. M., Goodman, R. P., & Turberfield, A. J. (2006). Single‐molecule protein encapsulation in a rigid DNA cage. Angewandte Chemie, 118(44), 7574-7577.

[12] Saccà, B., & Niemeyer, C. M. (2011). Functionalization of DNA nanostructures with proteins. Chemical Society Reviews, 40(12), 5910-5921.

[13] Wilner, O. I., Weizmann, Y., Gill, R., Lioubashevski, O., Freeman, R., & Willner, I. (2009). Enzyme cascades activated on topologically programmed DNA scaffolds. Nature nanotechnology, 4(4), 249-254.

[14] Delebecque, C. J., Lindner, A. B., Silver, P. A., & Aldaye, F. A. (2011). Organization of intracellular reactions with rationally designed RNA assemblies. Science, 333(6041), 470-474.

[15] Pierce, T. S. (2009). Crosslinking technical handbook. Thermo Fisher Scientific, Rockford, IL, USA.

[16] Zhang, Y. H. P. (2011). Substrate channeling and enzyme complexes for biotechnological applications. Biotechnology advances, 29(6), 715-725.

[17] Idan, O., & Hess, H. (2013). Origins of activity enhancement in enzyme cascades on scaffolds. ACS nano, 7(10), 8658-8665.

[18] Lee, H., DeLoache, W. C., & Dueber, J. E. (2012). Spatial organization of enzymes for metabolic engineering. Metabolic engineering, 14(3), 242-251.

[19] Chen, A. H., & Silver, P. A. (2012). Designing biological compartmentalization. Trends in cell biology, 22(12), 662-670.

[20] Ke, Y., Sharma, J., Liu, M., Jahn, K., Liu, Y., & Yan, H. (2009). Scaffolded DNA origami of a DNA tetrahedron molecular container. Nano letters, 9(6), 2445-2447.

[21] Iacovelli, F., Alves, C., Falconi, M., Oteri, F., Oliveira, C. L., & Desideri, A. (2014). Influence of the single‐strand linker composition on the structural/dynamical properties of a truncated octahedral DNA nano‐cage family. Biopolymers, 101(10), 992-999.

[22]Han, D., Pal, S., Nangreave, J., Deng, Z., Liu, Y., & Yan, H. (2011). DNA origami with complex curvatures in three-dimensional space. Science, 332(6027), 342-346.

[23] Falconi, M., Oteri, F., Chillemi, G., Andersen, F. F., Tordrup, D., Oliveira, C. L., ... & Desideri, A. (2009). Deciphering the structural properties that confer stability to a DNA nanocage. ACS nano, 3(7), 1813-1822.

[24] Funazukuri, T., Hirota, M., Nagatake, T., & Goto, M. (2000). Bioseparation Engineering, edited by Endo I., Nagamune T., Katoh S., Yonemoto T.

[25] Nfor, B. K., Verhaert, P. D., van der Wielen, L. A., Hubbuch, J., & Ottens, M. (2009). Rational and systematic protein purification process development: the next generation. Trends in biotechnology, 27(12), 673-679.

[26] D'Souza, R. N., Azevedo, A. M., Aires-Barros, M. R., Krajnc, N. L., Kramberger, P., Carbajal, M. L., ... & Fernández-Lahore, M. (2013). Emerging technologies for the integration and intensification of downstream bioprocesses. Pharmaceutical Bioprocessing, 1(5), 423-440.

[27] Grima, E. M., Belarbi, E. H., Fernández, F. A., Medina, A. R., & Chisti, Y. (2003). Recovery of microalgal biomass and metabolites: process options and economics. Biotechnology advances, 20(7), 491-515.

[28] Feng, D., Aldrich, C., & Tan, H. (2000). Removal of heavy metal ions by carrier magnetic separation of adsorptive particulates. Hydrometallurgy, 56(3), 359-368.

[29] Yavuz, C. T., Prakash, A., Mayo, J. T., & Colvin, V. L. (2009). Magnetic separations: from steel plants to biotechnology. Chemical Engineering Science, 64(10), 2510-2521.

[30] Lu, A. H., Salabas, E. E., & Schüth, F. (2007). Magnetic nanoparticles: synthesis, protection, functionalization, and application. Angewandte Chemie International Edition, 46(8), 1222-1244.

[31] Corchero, J. L., & Villaverde, A. (2009). Biomedical applications of distally controlled magnetic nanoparticles. Trends in biotechnology, 27(8), 468-476.

[32] Pierce, T. S. (2011). Thermo Scientific Particle Technology Product Catalog and Technical Reference Guide. Thermo Fisher Scientific, Freemont, CA, USA.

[33] Nestl, B. M., Nebel, B. A., & Hauer, B. (2011). Recent progress in industrial biocatalysis. Current opinion in chemical biology, 15(2), 187-193.

[34] Huang, L. Q., Wang, X. Y., & Ma, C. Y. (2013). Molecular Mechanism and Regulation on Biosynthesis of Active Ingredients of Medicinal Plants. InMolecular Pharmacognosy (pp. 185-218). Springer Netherlands.

[35] Ju, L. K., & Chase, G. G. (1992). Improved scale-up strategies of bioreactors.Bioprocess Engineering, 8(1-2), 49-53.

[36] Pollard, D. J., & Woodley, J. M. (2007). Biocatalysis for pharmaceutical intermediates: the future is now. TRENDS in Biotechnology, 25(2), 66-73.

[37] Young, E., & Alper, H. (2010). Synthetic biology: tools to design, build, and optimize cellular processes. BioMed Research International, 2010.

[38] Sharp, P. A., Cooney, C. L., A., K. M., Lees, J., Sasisekharan, S., Yaffe, M. B., Sur, M. (2011). MIT: The Convergence of the Life Sciences, Physical Sciences, and Engineering.

[39] Imam, S., Schäuble, S., Brooks, A. N., Baliga, N. S., & Price, N. D. (2015). Data-driven integration of genome-scale regulatory and metabolic network models. Frontiers in microbiology, 6.

[40] Towards 2020 science. Microsoft Research, 2006.

[41] Cacciuttolo, M. A., Shane, E., Oliver, C., Tsao, E., & Kimura, R. (2001). Scale-up considerations for biotechnology-derived products. Pharmaceutical Process Scale-Up, 95.

[42] Muller, F. L., & Latimer, J. M. (2009). Anticipation of scale up issues in pharmaceutical development. Computers & Chemical Engineering, 33(5), 1051-1055.

[43] Hooshangi, Sara, and William E. Bentley. "From unicellular properties to multicellular behavior: bacteria quorum sensing circuitry and applications."Current Opinion in Biotechnology 19.6 (2008): 550-555.

[44]Weiss, R. (2004, February). Challenges and opportunities in programming living cells. In Frontiers of Engineering: Reports on Leading-Edge Engineering from the 2003 NAE Symposium on Frontiers of Engineering (p. 121). National Academies Press.

[45] Delvigne, F., Boxus, M., Ingels, S., & Thonart, P. (2009). Bioreactor mixing efficiency modulates the activity of a prpoS:: GFP reporter gene in E. coli.Microb Cell Fact, 8, 15.

[46] Palomares, Laura A., Sandino Estrada-Moncada, and Octavio T. Ramírez. "Production of recombinant proteins." Recombinant Gene Expression. Humana Press, 2004. 15-51.

[47] Huisman, G. W., & Collier, S. J. (2013). On the development of new biocatalytic processes for practical pharmaceutical synthesis. Current opinion in chemical biology, 17(2), 284-292.

[48] Tufvesson, P., Fu, W., Jensen, J. S., & Woodley, J. M. (2010). Process considerations for the scale-up and implementation of biocatalysis. Food and Bioproducts Processing, 88(1), 3-11.

[49] Roberge, D. M., Gottsponer, M., Eyholzer, M., & Kockmann, N. (2009). Industrial design, scale-up, and use of microreactors. Chem. Today, 7, 8-11.

[50] Sheldon, R.A. (1994) Consider the environmental quotient. Chemotherapy, 24 (3), 38–47.

[51] Hermann, M., Kietzmann, M.U., Ivancic, M. et al. (2008) Alternative pig liver esterase (APLE) – cloning, identification and functional expression in Pichia pastoris of a versatile new biocatalyst. Journal of Biotechnology, 133 (3), 301–310.

[52] Griffiths, M. (2001) The Application of Biotechnology to Industrial Sustainability, OECD Publications, ISBN 92-64-19546-7.

[53] Wohlgemuth, R. (2010). Biocatalysis—key to sustainable industrial chemistry.Current opinion in biotechnology, 21(6), 713-724.

[54] Straathof, A. J., Panke, S., & Schmid, A. (2002). The production of fine chemicals by biotransformations. Current opinion in biotechnology, 13(6), 548-556.


Figure 1. Representation of different "black boxes". The different layers and input/outputs in a computational system (1.a) can be compared to the inputs and outputs of a production process in which the responsibles of the reactions are not known(1.b).

Figure 3. The diffusion of substrates and products is limited by scaffold geometry. Nanocages keep the enzymes together while allowing relatively free diffusion of substrates and products in comparison to other structures. Nanotubes and 2D scaffolds, thus, have a disadvantage regarding diffusion.