Opportunities for engineering outer membrane vesicles using synthetic biology approaches
Abstract
Gram-negative bacteria naturally shed lipid vesicles, which contain complex molecular cargoes, from their outer membrane. These outer membrane vesicles (OMVs) have important biological functions relating to microbial stress responses, microbiome regulation, and host-pathogen interactions. OMVs are also attractive vehicles for delivering drugs, vaccines, and other therapeutic agents because of their ability to interact with host cells and their natural immunogenic properties. OMVs are also set to have a positive impact on other biotechnological and medical applications including diagnostics, bioremediation, and metabolic engineering. We envision that the field of synthetic biology offers a compelling opportunity to further expand and accelerate the foundational research and downstream applications of OMVs in a range of applications including the provision of OMV-based healthcare technologies. In our opinion, we discuss how current and potential future synergies between OMV research and synthetic biology approaches might help to further accelerate OMV research and real-world applications for the benefit of animal and human health.
Keywords
Gram-negative bacteria naturally shed lipid vesicles, which contain complex molecular cargoes, from their outer membrane[1]. These outer membrane vesicles (OMVs) have diverse and important biological functions relating to microbial stress responses, and play a crucial role in intra- and inter-bacterial communication for microbiome regulation and host-pathogen interactions including immunomodulatory functions[2,3]. Essentially, OMVs can enable Gram-negative bacteria to respond to, and somewhat influence, their microenvironment[4]. Gram-positive bacteria (e.g., Bacillus subtilis) and mycolic acid-containing bacteria (e.g., Mycobacterium and Corynebacterium) also produce different types of membrane vesicles (MVs)[5,6], although these are not the focus of our opinion. Beyond their natural biological functions, OMVs might also serve biotechnological applications and are therefore being developed as therapeutics, human or animal vaccines, medical imaging and biosensing agents, or as scaffolds for metabolic engineering or bioremediation[7-14]. Mechanisms relating to OMV biogenesis/formation, and their molecular compositions (lipid, protein, nucleic acids, and small molecules) are being studied across many different bacteria and culture contexts (e.g., natural environment or bioreactor fermentation)[1]. This foundational understanding will likely be beneficial to the long-term development of OMV-based biotechnological applications. It is our opinion that synthetic biology bioengineering approaches could also help accelerate OMV foundational research and OMV-based biotechnological applications including the provision of OMV-based healthcare technologies[8,10,15-17].
Synthetic biology has emerged during the last several decades as an exciting interdisciplinary scientific field that seeks to systematically address biological complexity and to rationally engineer biological systems for useful purposes[18,19]. To this end, the field has established a suite of cutting-edge methodologies and tools, underpinned by an engineering framework and responsible innovation practices, that have helped accelerate many real-world applications[20-23]. On a fundamental level, synthetic biology employs an engineering framework around the concept of the design-build-test-learn (DBTL) cycle or the synthetic biology design cycle[18,22,24-27] [Figure 1]. The design cycle allows the optimisation of rationally designed biotechnologies and provides a strategy to address biological complexity[18,19,27]. Implicit within this framework is a focus on standardised experimental protocols and rigorous biological metrology[28,29]. This rigorous approach is also shared by the wider international extracellular vesicle research community in the form of research standards guidelines (e.g., MISEV2018) or technical research papers from the community[30,31]. However, we feel that further multi-disciplinary learning between the synthetic biology and EV fields regarding experimental design, protocols, research tools, and biological metrology would be beneficial to both fields. For example, synthetic biology has greatly expanded the throughput of the design cycle using automation (e.g., acoustic and liquid handling robotics platforms) to set up large-scale, multiparameter experiments[19,22,27,32]. These approaches reduce errors associated with manual pipetting and produce larger datasets that, especially in combination with design-of-experiment (DOE) or artificial intelligence (AI)-guided methodologies, can lead to deeper biological insights more quickly than conventional biological research workflows[33,34].
Figure 1. Synthetic biology approaches to outer membrane vesicle (OMV) engineering. The figure depicts synthetic biology engineering approaches and example biotechnologies that could be utilised to engineer OMV producing strains to improve OMV yields and/or the therapeutic cargos of microbially produced OMVs. AI: artificial intelligence; CDS: coding sequence; CRISPR/dCas9: clustered regularly interspaced short palindromic repeats (CRISPR)/endonuclease deficient CRISPR-associated protein 9 (dCas9); DOE: design of experiments; OMV: outer membrane vesicle.
In an OMV engineering context, a DBTL-cycle approach could be employed to systematically engineer bacterial strains with altered OMV cargoes. An interesting and relevant example of this was demonstrated by Zanella et al. in which they used a CRISPR/Cas9-based genome editing approach to systematically knock out 59 endogenous OMV-cargo protein genes in an engineered BL21(DE3)Δ60 Escherichia coli strain[15]. This study not only provided foundational insights into endogenous OMV protein cargo loading in E. coli BL21, but also demonstrated an engineering strategy to increase the level of recombinant proteins that can be loaded into the strains OMVs. These insights could be exploited to produce more effective OMV-based vaccines. Complementary to this approach, Alves et al. demonstrated that phosphotriesterase (PTE)-SpyCatcher and SpyTagged-OmpA transmembrane fusion proteins facilitated efficient packaging of PTE enzymes within OMVs[11], thereby expanding the utility of this important synthetic biology tool as a bioconjugation system for OMV engineering applications. While in another study, Eastwood et al. engineered a vesicle nucleating peptide derived from human α-synuclein to efficiently load a panel of OMV cargo proteins[35]. Such approaches could also conceivably facilitate more efficient loading of Cas9 into OMVs for medical applications. For example, OMVs have been utilised as a mechanism for delivering Cas9 to human microbial pathogens to elicit targeted and potent DNA damage. This route has been posited as a potential future therapeutic strategy to combat antimicrobial resistance[36]. It is also apparent that synthetic biology is developing many other genome editing tools [e.g., Transcription activator-like effector nucleases (TALENs), zinc-finger nucleases (ZFNs) and nucleobase deaminase enzymes][37], and gene expression regulation technologies (e.g., catalytically dead CRISPR/dCas9) [Figure 1][38,39] that could also be applied in future OMV engineering studies. One important application might be the use of sophisticated strain engineering approaches to finely tune bacterial/OMV lipopolysaccharide (LPS) content, the surface display of engineered polysaccharide antigens or the content of other immunomodulatory molecules to minimise unwanted cytotoxicity and maximise OMV vaccine efficacy[13-15,17,40,41]. Alternatively, OMVs from multiple different strains could also be pooled together to improve vaccine efficacy. Indeed, an OMV pooling strategy was recently employed to develop a poultry vaccine against avian pathogenic E. coli (APEC)[14]. OMV vaccines for human health have also been developed, including Bexsero®, a Neisseria meningitidis vaccine, that has received US FDA approval[10]. Other human and animal OMV-based vaccines are also in development[10,14].
Synthetic biology has also greatly expanded the number of gene regulatory elements (e.g., promoters) and other functional genetic elements (e.g., periplasmic localisation tags)[26,42], which, along with their modular (re-useable) nature, and potential for compatibility with high-throughput DNA assembly methods (e.g., Golden Gate)[18,43], creates almost endless possibilities for engineering OMV-producing strains with bespoke molecular cargoes. Furthermore, cell-free protein synthesis systems (CFPS), which utilise isolated cellular transcription/translation machinery, could be used to prototype and test many different assembled expression plasmids or cargo designs to accelerate future OMV engineering design cycles[22,44] [Figure 1]. Furthermore, recent innovations in protein design and folding, including AlphaFold[45], protein large language models (e.g., ESM-2)[46], and other powerful protein structure/function design tools[47,48], could be applied to future OMV studies to engineer entirely de novo designed OMV cargo or membrane fusion-proteins. By extension, recent advancements in bacterial metabolic engineering strategies[12,49], including codon reassignment and non-natural amino acid incorporation[50-52], and xeno nucleic acids (XNAs)[53], may lead to powerful OMV cargoes and therapeutic modalities that are entirely synthetic and orthogonal to the production host-cells’ biochemistry. In the near future, the convergence of synthetic biology technologies with OMV engineering approaches may lead to the emergence of synthetic membrane vesicles (MVs) from entirely engineered cells[54,55].
This leads to the interesting question of whether synthetic cell-derived MVs might also serve as intercellular communication vehicles to coordinate synthetic cell consortia. While significant technical challenges remain before synthetic cell-derived MVs become routine, there is scope for fruitful collaborations between OMV researchers and the synthetic cell communities. For example, improvements in methods to exogenously load small molecule, protein or nucleic acid cargoes into lipid vesicles, whether they are OMVs or synthetic cells, will be useful to both fields[19,55-57]. Indeed, it should also be noted that the origins of future exogenous cargo molecules might also be the product of synthetic biology-based manufacturing processes[12,19,23]. Contemporary OMV engineering efforts are already making an impact across disparate applications. For example, OMVs loaded with Gentamicin, the receptor binding domain of the
CONCLUSION
OMVs hold great promise as future therapeutics, vaccines, diagnostics, and industrial or pharmaceutical manufacturing agents. Indeed, several OMV-based vaccines are already in use. We envision that future convergences between synthetic biology and OMV research will likely expand future OMV-based applications. However, there are foundational knowledge gaps in our understanding of OMV molecular heterogeneity and biogenesis in different contexts. Furthermore, manufacturing OMVs at suitable yields, purity and bioactivities is also challenging and may require additional innovations in OMV isolation technologies, engineering approaches and OMV characterisation methods. However, we envision that a combination of synthetic biology and OMV tools and research approaches will help both fields to overcome these challenges, thereby accelerating the translation of OMVs toward additional real-world applications for the benefit of animal and human health.
DECLARATIONS
Author’s contributionsWriting - original draft: Kelwick RJR, Webb AJ, Freemont PS
Writing - review & editing: Kelwick RJR, Webb AJ, Freemont PS
Availability of data and materialsNot applicable.
Financial support and sponsorshipWe thank the Biotechnology and Biological Sciences Research Council (BBSRC) for a developing engineering biology breakthrough ideas grant (BB/W012987/1); We also acknowledge support from The Engineering and Physical Sciences Research Council (EPSRC), BBSRC and the Future Biomanufacturing Research Hub (FBRH) at The University of Manchester for our Future BRH Award (EP/S01778X/1).
Conflict of interestAll authors declared that there are no conflicts of interest.
Ethical approval and consent to participateNot applicable.
Consent for publicationNot applicable.
Copyright© The Author(s) 2023.
REFERENCES
1. Schwechheimer C, Kuehn MJ. Outer-membrane vesicles from gram-negative bacteria: biogenesis and functions. Nat Rev Microbiol 2015;13:605-19.
2. Cecil JD, Sirisaengtaksin N, O'Brien-Simpson NM, Krachler AM. Outer membrane vesicle-host cell interactions. Microbiol Spectr 2019:7.
3. Toyofuku M, Nomura N, Eberl L. Types and origins of bacterial membrane vesicles. Nat Rev Microbiol 2019;17:13-24.
4. Olsen I, Amano A. Outer membrane vesicles - offensive weapons or good Samaritans? J Oral Microbiol 2015;7:27468.
5. Nagakubo T, Nomura N, Toyofuku M. Cracking open bacterial membrane vesicles. Front Microbiol 2019;10:3026.
6. Brown L, Wolf JM, Prados-Rosales R, Casadevall A. Through the wall: extracellular vesicles in Gram-positive bacteria, mycobacteria and fungi. Nat Rev Microbiol 2015;13:620-30.
7. Huang Y, Nieh MP, Chen W, Lei Y. Outer membrane vesicles (OMVs) enabled bio-applications: a critical review. Biotechnol Bioeng 2022;119:34-47.
8. Wang S, Gao J, Wang Z. Outer membrane vesicles for vaccination and targeted drug delivery. Wiley Interdiscip Rev Nanomed Nanobiotechnol 2019;11:e1523.
9. Li Y, Wu J, Qiu X, et al. Bacterial outer membrane vesicles-based therapeutic platform eradicates triple-negative breast tumor by combinational photodynamic/chemo-/immunotherapy. Bioact Mater 2023;20:548-60.
10. Alexander LM, van Pijkeren JP. Modes of therapeutic delivery in synthetic microbiology. Trends Microbiol 2023;31:197-211.
11. Alves NJ, Turner KB, Daniele MA, et al. Bacterial nanobioreactors-directing enzyme packaging into bacterial outer membrane vesicles. ACS Appl Mater Interfaces 2015;7:24963-72.
12. Yang D, Park SY, Lee SY. Production of rainbow colorants by metabolically engineered escherichia coli. Adv Sci 2021;8:e2100743.
13. Liu H, Geng Z, Su J. Engineered mammalian and bacterial extracellular vesicles as promising nanocarriers for targeted therapy. Extracell Vesicles Circ Nucleic Acids 2022;3:63-86.
14. Hu R, Li J, Zhao Y, et al. Exploiting bacterial outer membrane vesicles as a cross-protective vaccine candidate against avian pathogenic escherichia coli (APEC). Microb Cell Fact 2020;19:119.
15. Zanella I, König E, Tomasi M, et al. Proteome-minimized outer membrane vesicles from Escherichia coli as a generalized vaccine platform. J Extracell Vesicles 2021;10:e12066.
16. Thapa HB, Müller AM, Camilli A, Schild S. An intranasal vaccine based on outer membrane vesicles against SARS-CoV-2. Front Microbiol 2021;12:752739.
17. Li R, Liu Q. Engineered bacterial outer membrane vesicles as multifunctional delivery platforms. Front Mater 2020;7:202.
18. Kelwick R, MacDonald JT, Webb AJ, Freemont P. Developments in the tools and methodologies of synthetic biology. Front Bioeng Biotechnol 2014;2:60.
19. Brooks SM, Alper HS. Applications, challenges, and needs for employing synthetic biology beyond the lab. Nat Commun 2021;12:1390.
20. Voigt CA. Synthetic biology 2020-2030: six commercially-available products that are changing our world. Nat Commun 2020;11:6379.
21. Liew FE, Nogle R, Abdalla T, et al. Carbon-negative production of acetone and isopropanol by gas fermentation at industrial pilot scale. Nat Biotechnol 2022;40:335-44.
22. Kelwick RJR, Webb AJ, Freemont PS. Biological materials: the next frontier for cell-free synthetic biology. Front Bioeng Biotechnol 2020;8:399.
23. El Karoui M, Hoyos-Flight M, Fletcher L. Future trends in synthetic biology-a report. Front Bioeng Biotechnol 2019;7:175.
24. Carbonell P, Jervis AJ, Robinson CJ, et al. An automated design-build-test-learn pipeline for enhanced microbial production of fine chemicals. Commun Biol 2018;1:66.
25. Opgenorth P, Costello Z, Okada T, et al. Lessons from two design-build-test-learn cycles of dodecanol production in escherichia coli aided by machine learning. ACS Synth Biol 2019;8:1337-51.
26. Casas A, Bultelle M, Motraghi C, Kitney R. Removing the bottleneck: introducing cMatch - a lightweight tool for construct-matching in synthetic biology. Front Bioeng Biotechnol 2021;9:785131.
27. Sanders LM, Scott RT, Yang JH, et al. Biological research and self-driving labs in deep space supported by artificial intelligence. Nat Mach Intell 2023;5:208-19.
28. Beal J, Goñi-Moreno A, Myers C, et al. The long journey towards standards for engineering biosystems: are the molecular biology and the biotech communities ready to standardise? EMBO Rep 2020;21:e50521.
29. Kelly JR, Rubin AJ, Davis JH, et al. Measuring the activity of BioBrick promoters using an
30. Théry C, Witwer KW, Aikawa E, et al. Minimal information for studies of extracellular vesicles 2018 (MISEV2018): a position statement of the international society for extracellular vesicles and update of the MISEV2014 guidelines. J Extracell Vesicles 2018;7:1535750.
31. Dauros Singorenko P, Chang V, Whitcombe A, et al. Isolation of membrane vesicles from prokaryotes: a technical and biological comparison reveals heterogeneity. J Extracell Vesicles 2017;6:1324731.
32. Jessop-Fabre MM, Sonnenschein N. Improving reproducibility in synthetic biology. Front Bioeng Biotechnol 2019;7:18.
33. Gilman J, Walls L, Bandiera L, Menolascina F. Statistical design of experiments for synthetic biology. ACS Synth Biol 2021;10:1-18.
34. Beardall WAV, Stan GB, Dunlop MJ. Deep learning concepts and applications for synthetic biology. GEN Biotechnol 2022;1:360-71.
35. Eastwood TA, Baker K, Streather BR, et al. High-yield vesicle-packaged recombinant protein production from
36. Tao S, Chen H, Li N, Liang W. The application of the CRISPR-cas system in antibiotic resistance. Infect Drug Resist 2022;15:4155-68.
37. Porto EM, Komor AC, Slaymaker IM, Yeo GW. Base editing: advances and therapeutic opportunities. Nat Rev Drug Discov 2020;19:839-59.
38. Qi LS, Larson MH, Gilbert LA, et al. Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression. Cell 2013;152:1173-83.
39. Ceroni F, Boo A, Furini S, et al. Burden-driven feedback control of gene expression. Nat Methods 2018;15:387-93.
40. Tian H, Li B, Xu T, et al. Outer membrane vesicles derived from salmonella enterica serotype typhimurium can deliver shigella flexneri 2a O-polysaccharide antigen to prevent shigella flexneri 2a infection in mice. Appl Environ Microbiol 2021;87:e0096821.
41. Gasperini G, Alfini R, Arato V, et al. Salmonella paratyphi a outer membrane vesicles displaying vi polysaccharide as a multivalent vaccine against enteric fever. Infect Immun 2021:89.
42. Plahar HA, Rich TN, Lane SD, et al. Bioparts-a biological parts search portal and updates to the ICE parts registry software platform. ACS Synth Biol 2021;10:2649-60.
43. Haines MC, Carling B, Marshall J, et al. Basicsynbio and the BASIC SEVA collection: software and vectors for an established DNA assembly method. Synth Biol 2022;7:ysac023.
44. Kelwick RJR, Webb AJ, Heliot A, Segura CT, Freemont PS. Opportunities to accelerate extracellular vesicle research with cell‐free synthetic biology. J of Extracellular Bio 2023;2:e90.
45. Jumper J, Evans R, Pritzel A, et al. Highly accurate protein structure prediction with AlphaFold. Nature 2021;596:583-9.
46. Lin Z, Akin H, Rao R, et al. Evolutionary-scale prediction of atomic-level protein structure with a language model. Science 2023;379:1123-30.
47. Wang J, Lisanza S, Juergens D, et al. Scaffolding protein functional sites using deep learning. Science 2022;377:387-94.
48. Dauparas J, Anishchenko I, Bennett N, et al. Robust deep learning-based protein sequence design using ProteinMPNN. Science 2022;378:49-56.
49. Zawada JF, Burgenson D, Yin G, et al. Cell-free technologies for biopharmaceutical research and production. Curr Opin Biotechnol 2022;76:102719.
50. Dumas A, Lercher L, Spicer CD, Davis BG. Designing logical codon reassignment - Expanding the chemistry in biology. Chem Sci 2015;6:50-69.
51. Young TS, Schultz PG. Beyond the canonical 20 amino acids: expanding the genetic lexicon. J Biol Chem 2010;285:11039-44.
52. Rezhdo A, Islam M, Huang M, Van Deventer JA. Future prospects for noncanonical amino acids in biological therapeutics. Curr Opin Biotechnol 2019;60:168-78.
53. Duffy K, Arangundy-Franklin S, Holliger P. Modified nucleic acids: replication, evolution, and next-generation therapeutics. BMC Biol 2020;18:112.
54. Xu C, Martin N, Li M, Mann S. Living material assembly of bacteriogenic protocells. Nature 2022;609:1029-37.
55. Lussier F, Staufer O, Platzman I, Spatz JP. Can bottom-up synthetic biology generate advanced drug-delivery systems? Trends Biotechnol 2021;39:445-59.
56. Chen C, Sun M, Wang J, et al. Active cargo loading into extracellular vesicles: Highlights the heterogeneous encapsulation behaviour. J Extracell Vesicles 2021;10:e12163.
57. Chen H, Zhou M, Zeng Y, et al. Recent advances in biomedical applications of bacterial outer membrane vesicles. J Mater Chem B 2022;10:7384-96.
Cite This Article
How to Cite
Kelwick, R. J. R.; Webb A. J.; Freemont P. S. Opportunities for engineering outer membrane vesicles using synthetic biology approaches. Extracell. Vesicles. Circ. Nucleic. Acids. 2023, 4, 255-61. http://dx.doi.org/10.20517/evcna.2023.21
Download Citation
Export Citation File:
Type of Import
Tips on Downloading Citation
Citation Manager File Format
Type of Import
Direct Import: When the Direct Import option is selected (the default state), a dialogue box will give you the option to Save or Open the downloaded citation data. Choosing Open will either launch your citation manager or give you a choice of applications with which to use the metadata. The Save option saves the file locally for later use.
Indirect Import: When the Indirect Import option is selected, the metadata is displayed and may be copied and pasted as needed.
Comments
Comments must be written in English. Spam, offensive content, impersonation, and private information will not be permitted. If any comment is reported and identified as inappropriate content by OAE staff, the comment will be removed without notice. If you have any queries or need any help, please contact us at support@oaepublish.com.