Добавил:
kiopkiopkiop18@yandex.ru t.me/Prokururor I Вовсе не секретарь, но почту проверяю Опубликованный материал нарушает ваши авторские права? Сообщите нам.
Вуз: Предмет: Файл:
Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5886_Библиотеки_им_академика_М_И_Перельмана.pdf
Скачиваний:
0
Добавлен:
02.09.2026
Размер:
21 Мб
Скачать
40
A. K. Sato and S. Rife
There is currently signicant interest in the development of single-domain heavy-chain (VHH) biologics owing to their antibody-like properties and smaller size (affording them distinct pharmacokinetics relative to full-length antibodies). Assembling VHH libraries can be challenging with trimers due to the potential for truncation. Truncated oligonucleotides can then lead to a diminished percentage of full-length VHH candidates and the need for increased screening to ensure that all full-length variants are tested.
With trimers, it is alsodifcult to avoid liability motifs that can result in instabil­ity of biologics following post-translational modications or isomerization. In order to avoid motifs with trimers, certain amino acids would need to be avoided to elimi­nate the possibility of unwanted amino acid pairings that would create an undesir­able motif.
Direct synthesis, on the other hand, has enabled a much higher degree of preci­sion and efciency. Through solid-phase synthesis along with miniaturized chemis­try, companies like Twist Bioscience have made it possible to synthesize oligonucleotides without randomization. By deliberately adding every nucleotide in a growing strand, direct synthesis can be programmed to generate combinatorial variant libraries containing uniform variant representation and prespecied amino acid ratios (Fig.2.4).
The improved accuracy and efciency gained through direct synthesis has enabled researchers to focus their resources on generating and testing millions of rationally designed antibody variants. In so doing, direct synthesis has improved the scale of antibody discovery by allowing parallelization—rather than only creating a
Fig. 2.4 Amino acid distribution after synthesis with NNK, Trimer, and direct synthesis. When compared to NNK and Trimer synthesis, libraries created with direct synthesis technology (Twist) showed less than 1% deviation from the designed amino acid frequency (y-axis). (Data produced by Twist Bioscience)
2 Synthetic Biology inDrug Development andBeyond
41
small handful of desired antibodies at a time, millions can be rapidly produced and screened in parallel.
Importantly, such libraries need not be full-length antibodies. As researchers are primarily interested in identifying antibodies with a specic and strong afnity for their target of interest, resources can be conserved by limiting synthesis to antibody fragments that contain CDR loops, such as VHH, single-chain variable fragments (scFv), and fragment antigen-binding regions (Fabs). This approach opens the door to high-throughput screening opportunities.
As with other synthesis methods, direct synthesis is not without its hurdles. Highly parallel direct oligonucleotide synthesis requires substantial infrastructure and automation. As such, these methods are often more expensive than degenerate methods and, like trimers, must contend with nucleotide coupling efciencies to ensure uniform representation. Therefore, careful design and quality control (often through next-generation sequencing) is needed, further driving up costs. However, direct synthesis has greatly decreased the costs associated with DNA synthesis and will likely continue to do so as the technology advances [54].
Phage Display
Converting synthetic DNA libraries into screen-ready antibody libraries requires cellular machinery. Therefore, synthesized libraries must be inserted into a chassis organism whose internal machinery can be taken advantage of to produce antibody fragments.
Following DNA synthesis, antibody sequences can be assembled in plasmid or phagemid vectors and transduced into a display system. In these systems, antigen­binding fragments are heterologously expressed in a chassis organism such as a bacteriophage, yeast, or bacteria cell. Importantly, these antibody fragments are fused to a native surface protein within the chassis, enabling surface expression of the fragment [55, 56].
Phage display is the most commonly used display system in antibody discovery and development owing to its ease of use and scale. This system utilizes bacterio­phages—typically M13 bacteriophage—that selectively infects E. coli. For M13 bacteriophage, antibody fragments can be assembled into phagemid vectors as fusion proteins with one of the phage’s ve surface proteins. Importantly, the phagemid vector contains genetic elements that enable it to be enclosed in the viral capsid during replication [55].
The resulting bacteriophage will express antibody fragments on its surface while also containing phagemid vectors within. Selection is then performed by rst immo­bilizing puried antigens on solid surfaces, such as nitrocellulose membranes, poly­styrene plates, magnetic beads, or column matrices. Then, a phage library corresponding to the synthesized antibody library can be exposed to the immobi­lized antigen. Successive cycles of washing will eliminate all unbound phages, leav­ing just those phages that express high-afnity antigen-binding fragments (Fig.2.5).
High-afnity binders can then be recovered with the use of myriad elution buf­fers. Because the eluted phages each contain a phagemid, they can be transduced into E. coli and subsequently sequenced to determine which antibody sequences correspond to high-afnity binders.
42
A. K. Sato and S. Rife
Fig. 2.5 Phage display for antibody discovery. Workow for the discovery and optimization of antibodies using phage display. Helper phages may be needed to ensure production of engineered bacteriophages. (Figure adapted from “Phage Display Panning,” by BioRender.com [2022]. Retrieved from https://app.biorender.com/biorender- templates)
Phage display screens can be used to test libraries as large as 1010 unique anti­body fragments, enabling researchers to rapidly home in on antibody sequences with desired binding properties [55, 56]. In contrast to immunization approaches, invitro display systems can be used to develop biologics against highly toxic and non-immunogenic targets.
Though phage display has clear advantages over hybridoma technology, antibod­ies discovered through phage display often require substantial optimization. Replicating invitro the immune system’s ability to rapidly optimize antibodies for given antigens is difcult. Without comprehensive optimization, phage-derived antibodies may be prone to invivo aggregation, low levels of expression, and other issues that limit the antibody’s clinical utility [57]. However, invitro optimization
2 Synthetic Biology inDrug Development andBeyond
43
systems are advancing and may reduce developability concerns stemming from phage display in the near future.
In the meantime, phage display remains a powerful discovery tool. As of August 2020, 70 phage-derived antibodies had advanced to clinical trials, 14 of which have already been approved [56].
Similar display systems have been developed with other chassis organisms, such as S. cerevisiae [55]. Herein, synthetic DNA encoding antibody fragments are trans- fected into the yeast where they integrate with the yeast’s cell wall, akin to the integration that occurs in bacteriophages. These eukaryotic display systems can be useful as they replicate post-transcriptional modications that may affect antibody performance in human cells, such as glycosylation. While yeast glycosylation pat­terns may differ from what is observed in humans, yeast cells can be engineered to express human glycosylation machinery. Useful as it is, yeast display suffers from decreased efciencies that limit its scale to approximately 108 antibody fragments per experiment.
There are many more display systems worth diving into, and we encourage you to read Mahdavi etal.’s excellent overview in the International Journal of Biological Macromolecules to learn more [55].

2.6 CAR-T Cell Therapies

One of the most recognized therapeutic applications of synthetic biology is in the development of cell therapies broadly and chimeric antigen receptor (CAR) pre­senting T-cells specically. Conceptually, cell therapies aim to endow an organism with enhanced immune cells, whether those are stem cells lacking pathogenic muta­tions or, in the case of CAR-T cells, differentiated cells with specic and potent pathogen targeting abilities. In contrast to the transient nature of antibodies and small molecules, cell therapies have the potential to help patients indenitely, pro­viding lasting protection against recurrent malignancies or viruses like HIV [5860].
Among the many different cell therapies, CAR-T cell technology has seen remarkable advancement in recent years, driven largely by improvements in syn­thetic biology (Fig.2.6).
T-cells are a class of lymphocytes that play a critical role in adaptive immunity [60]. Born in the thymus, naive T-cells roam the body awaiting activation. Unlike B-cells, which recognize pathogens through antibodies, T-cell activation is initiated when a unique cell surface protein—the T-cell receptor (TCR)—recognizes a major histocompatibility complex (MHC) protein displaying an antigenic peptide. This, combined with cascading signals from costimulatory factors, prompts T-cells to release a slew of cytokines that, depending on the type of T-cell, are often proin­ammatory [6163].
T-cells have the ability to direct adaptive immune cells against specic patho­gens and thus have signicant potential in therapeutic applications. Like antibodies, the human TCR repertoire is extremely diverse owing to V(d)J recombination. But
44
Fig. 2.6 CAR-T cell therapy overview. Workow for CAR-T cell therapy. T-cells are isolated from donor or patient blood and engineered to express a chimeric antigen receptor targeting tumor­cell- specic antigens. After successive rounds of growth, the engineered T-cells can then be rein­fused into the patient to affect therapeutic benets. (Reprinted from “CAR T Cell Therapy Overview,” by BioRender.com [2022]. Retrieved from https://app.biorender.com/biorender-
templates)
A. K. Sato and S. Rife
while a T-cell may have the ability to recognize antigens, it must do so when the antigenic peptide is in complex with an MHC protein [63]. Because of this, research­ers developing cell therapies based on T-cells would need to match highly antigen­specic T-cells against specic antigen-presenting cells together to enable a potent therapy. Or a simpler approach is to engineer therapeutic T-cells using synthetic biology.
In the late 1980s, researchers at multiple universities began engineering T-cells to express a synthetic fusion protein that combined antibody variable domains with T-cell receptor signaling domains [64, 65]. The resulting chimeric protein could thus recognize antigens with antibody-like specicity and, upon binding, elicit immunogenic activity from the host T-cell. These early experiments are broadly considered the rst demonstrations of CAR-T technology [66].
Importantly, the inclusion of antibody variable domains in CARs enables antigen recognition without the involvement of MHC proteins; and, the addition of a costimulatory factor (CD3ζ) enables the chimeric protein to elicit T-cell activation without MHC complex recognition on antigen-presenting cells [66]. Collectively, these modications make it possible to aim T-cells at specic antigens, such as pro­teins uniquely present on the surface of cancer cells, which can then independently mount an immune response.
The power of CAR-T cells was recognized around the world in 2012 when 6-year-old Emily Whitehead became the rst child to receive CAR-T therapy [67].
2 Synthetic Biology inDrug Development andBeyond
45
Emily had undergone 16months of intermittent chemotherapy, but the acute B-cell lymphoblastic leukemia that owed through her veins resisted treatment. With no other options, Emily was enlisted in a clinical trial to test the effect of a new CAR-T therapy, known as tisagenlecleucel (also referred to as Kymriah). T-cells from Emily’s body were removed and transduced with genes carrying a synthetic CAR that targeted the cell surface protein CD19. It has been more than 10years since her treatment, and Emily remains cancer free.
While both promising and inspiring, it is also a warning: following treatment, Emily’s body responded with a cytokine storm that nearly killed her. Cell therapies come with a substantial risk of inducing a potentially lethal condition known as cytokine release syndrome (CRS). The cause for critical side effects in cell therapies can be multifaceted. CRS can be induced through an overwhelming CAR-induced on-target, on-tumor inammatory reaction. Careful design and validation of the CAR for a given target and therapeutic indication is key for development of safe and efcacious therapies.
Beyond designing the synthetic receptor, the cellular vehicle that the CAR is inserted into plays a major role in drug development. While autologous therapies focus on engineering a patient’s own cells, allogeneic therapeutics offer the ability to build therapies with broader accessibility by using engineered cells from donors (discussed further below). However, such an option raises additional requirements in terms of design, engineering, and functional evaluation of cells. In contrast to autologous therapies, allogeneic therapies must take into consideration graft- versus­host disease (GVHD)—a condition wherein donor immune cells attack healthy host tissues [68]. Similarly, the engineered cells are at risk of being rejected by the host’s body.
The development of safe and effective CARs thus requires careful and extensive optimization to ensure both safety, specicity, and efcacy. Fortunately, many of the tools that characterize synthetic biology can be leveraged during CAR development.
Antibody display systems, for example, enable large-scale and high-throughput screening of potential antigen-binding domains. Once identied as specic for the target antigen, DNA coding for binding domains can be synthesized and assembled into a CAR gene.
Subsequent optimization will be required, wherein variations in antigen-binding domains, hinge and transmembrane domains, and costimulatory factor combina­tions are tested. This is because cellular response to CAR-antigen binding is highly context specic, and alterations in the exibility of transmembrane domains, as well as the intracellular environment, can alter downstream signaling. Therefore, researchers will need to generate and express combinatorial variant CAR libraries for iterative rounds of optimization [69, 70].
As with antibody discovery, the precise and large-scale production of synthetic DNA and the combinatorial assembly of variants can accelerate CAR-T develop­ment (Fig.2.7).
In some allogeneic therapies, even when CARs are optimized to be highly spe­cic, patients are still at risk for GVHD.This is because T-cells are trained to rec­ognize foreign cells through mismatches in MHC proteins (the human equivalent of
46
Fig. 2.7 Creation of chimeric antigen receptor and T-cell receptor libraries via combinatorial assembly. Through combinatorial assembly, user-dened combinations of gene fragments can be shufed together to create highly uniform screening libraries that enable comprehensive screening of the variant space and the discovery of CAR formats with novel functionalities
A. K. Sato and S. Rife
HLA proteins). It is thus important for donors and patients to carry similar HLA proles [71].
One approach to avoid GVHD is to use the patient’s own cells, as in the case of Emily Whitehead. This is known as autologous cell therapy. However, the patient’s immune cells may not be suitable for engineering due to the effects of previous therapeutics or the pathogen/malignancy affecting the patient.
In these situations, physicians may opt for allogeneic CAR-T cell therapy wherein T-cells are collected from a healthy donor, engineered to express the syn­thetic CAR, and then transfused into the patient. The risk of GVHD is signicant in allogeneic CAR-T cell therapy. And while supplementary chemotherapies are being explored to mitigate the risks of GVHD, and HLA matching is possible, the risks remain.
Another option is to use gene editing technology to engineer T-cell stocks that do not express HLA proteins, or else express specic HLA proles. These allogeneic T-cells could then serve as a repository, off-the-shelf option for researchers and physicians to access when needed. Research into this possibility is ongoing and holds signicant promise. Currently, CAR-T cells are generated rapidly, providing little time for cells to be optimized. However, if T-cell stocks can be made, research­ers may have ample time to engineer CAR-T cells that target multiple pathogenic antigens by expressing multiple different CARs [72].
The CAR-T therapy that saved Emily Whitehead’s life was approved by the FDA for the autologous treatment of adult patients with relapsed or refractory follicular lymphoma after two or more lines of therapy [73]. While a substantial landmark for synthetic biology, much more research is needed to develop this technology. For
2 Synthetic Biology inDrug Development andBeyond
47
instance, CAR-T cells are not yet durable enough to provide lifelong immunity, and the intense immunological side effects will need to be contended with.
To this end, the success of CAR-T cell therapy has spurred interest in similar cell therapies [74]. One such therapy leverages natural killer (NK) cells—a type of peripheral leukocyte with potent cytotoxic abilities. Unlike T-cells, NK cells do not become activated against targets based on T-cell receptor-antigen binding. Instead, NK cells are under a dynamic state of intracellular signaling that suppresses activa­tion. However, when exposed to a myriad of contextual signals in the cell’s micro­environment that decrease suppression and enable cell-killing, cells that downregulate self-identifying HLA proteins, for example, are more likely to be tar­geted by NK cells [75, 76].
Interest in the use of NK cells for CAR therapy stems from a growing body of evidence that shows CAR-NK cells are less likely to induce CRS and GVHD (owing to a different cytokine release prole relative to T-cells), are capable of potent on­tumor cell-killing, and may affect cytotoxicity independent of CAR-antigen binding (through natural activation by the tumor microenvironment) [76]. With a reduced risk of CRS and GVHD, CAR-NK cells may prove to be better suited for off-the­shelf, allogeneic cell therapy development.
As with CAR-T cells, CAR-NK cell therapy faces several challenges related to transduction efciency, ex vivo expansion of engineered cells, tumor evolution toward the loss of CAR-targeted antigens, and more [76]. As such, development of CAR-NK will similarly require extensive preclinical optimizations in CAR design and engineering methods.
Nonetheless, development of both CAR-T and CAR-NK therapies represents shining examples of synthetic biology and its application in therapeutic develop­ment. It is likely that the number of clinical trials testing either CAR-T and CAR-NK will continue to increase as advances in synthetic biology continue to expand the scale and throughput of preclinical development.
Notably, there are many additional cell therapies that are worth exploring. The reader is encouraged to read more on cell therapies in a recent review by Wang etal. [74].

2.7 Conclusion

Synthetic biology is an expansive eld, one that aims to solve many of the world’s problems through the engineering of biological systems. Though relatively new, the eld has already made a substantial impact on modern drug discovery and the advancement of biologics research. In the preceding sections, we have attempted to provide a brief overview of this impact, highlighting choice contributions where possible. We have undoubtedly left many details and areas of interest out of this discussion, not for a lack of importance but rather in service of brevity.
While there is still much to be covered, there are some key concepts that we have tried to emphasize. When precisely synthesized, synthetic DNA can be a versatile
48
A. K. Sato and S. Rife
tool in the synthetic biologist’s toolkit. Novel genes can be rapidly assembled and, through cloning, inserted into a chassis organism. This process represents a syn­thetic dogma that drives modern drug development in a myriad of ways.
CRISPR-Cas systems are an excellent example. The CRISPR-Cas complex is a synthetic creation, modied from a bacterial immune system and used extensively for gene editing. Among its many uses, CRISPR-Cas affords researchers the ability to carry out functional genomic screening on a large scale, such that individual genes can be systematically perturbed across the entire genome within a single screen [77]. Such a study can reveal key genes involved in disease progression and thus potential therapeutic targets. To do this, synthetic DNA coding the CRISPR­Cas complex will be synthesized, assembled, and inserted into the cell line of inter­est for high-resolution study.
Beyond target identication and validation, synthetic biology is greatly advanc­ing our ability to discover therapeutic small molecules and biologics. Secondary metabolites, for example, are produced in myriad organisms and have proven to be powerful sources of therapeutic small molecules. However, screening of secondary metabolites has been severely limited. With complex structures and often low natu­ral concentrations, secondary metabolites can be difcult to detect and harder to screen. As such, discovery efforts are largely limited to metabolites produced in large quantities or in organisms that can be easily cultured in the laboratory setting.
Synthetic biology offers a way to greatly expand the scope of these efforts. Once described, the molecular pathways—often identied in biosynthetic gene clusters— that produce secondary metabolites can be reconstituted in chassis organisms and leveraged for the large-scale production of diverse secondary metabolite libraries. Such libraries have already been used to surface promising small molecules.
DNA synthesis, cloning, and expression in chassis organisms drives therapeutic antibody discovery, as well. Advances in DNA synthesis technology have made it possible to precisely and rapidly engineer millions of unique DNA sequences. These in turn can be assembled into synthetic antibody libraries whose diversity extends beyond natural repertoires, providing researchers with a unique opportunity to design, discover, and optimize novel therapeutic antibodies.
In short, it is clear that synthetic biology is a versatile eld and one that is inte­gral to modern drug development.

References

1. Mary Wollstonecraft Shelley (1831) Frankenstein
2. Hale V etal (2007) Microbially derived Artemisinin: a biotechnology solution to the global problem of access to affordable antimalarial drugs. Am J Trop Med Hyg 77(6_Suppl):198–202.
https://doi.org/10.4269/ajtmh.2007.77.198
3. Peplow M (2016) Synthetic biology’s rst malaria drug meets market resistance. Nature 530(7591):389–390. https://doi.org/10.1038/530390a
4. Septembre-Malaterre A etal (2020) Artemisia annua, a traditional plant brought to light. Int J Mol Sci 21(14):4986. https://doi.org/10.3390/ijms21144986
2 Synthetic Biology inDrug Development andBeyond
5. Paddon CJ, Keasling JD (2014) Semi-synthetic artemisinin: a model for the use of synthetic biology in pharmaceutical development. Nat Rev Microbiol 12(5):355–367. https://doi.
org/10.1038/nrmicro3240
6. Voigt CA (2020) Synthetic biology 2020–2030: six commercially-available products that are changing our world. Nat. Commun 11(1):6379. https://doi.org/10.1038/s41467- 020- 20122- 2
7. Cameron D, Ewen et al (2014) A brief history of synthetic biology. Nat Rev Microbiol 12(5):381–390. www.nature.com/articles/nrmicro3239/. https://doi.org/10.1038/nrmicro3239
8. van den Belt H (2009) Playing God in Frankenstein’s footsteps: synthetic biology and the meaning of life. Nanoethics 3(3):257–268. link.springer.com/article/10.1007%2Fs11569- 009-
0079- 6. https://doi.org/10.1007/s11569- 009- 0079- 6
9. Hughes RA, Ellington AD (2017) Synthetic DNA synthesis and assembly: putting the synthetic in synthetic biology. Cold Spring Harb Perspect Biol 9(1):a023812. https://doi.org/10.1101/
cshperspect.a023812
10. Chao R etal (2014) Recent advances in DNA assembly technologies. FEMS Yeast Res 15:1–9.
https://doi.org/10.1111/1567- 1364.12171
11. David F et al (2021) A perspective on synthetic biology in drug discovery and develop­ment—current impact and future opportunities. SLAS Discov 26(5):581–603. https://doi.
org/10.1177/24725552211000669
12. Beitz AM etal (2022) Synthetic gene circuits as tools for drug discovery. Trends Biotechnol 40(2):210–225. https://doi.org/10.1016/j.tibtech.2021.06.007
13. Ausländer S, Fussenegger M (2013) From gene switches to mammalian designer cells: present and future prospects. Trends Biotechnol 31(3):155–168. https://doi.org/10.1016/j.
tibtech.2012.11.006
14. Goñi-Moreno A, Amos M (2012) A recongurable NAND/nor genetic logic gate. BMC Syst Biol 6(1):126. https://doi.org/10.1186/1752- 0509- 6- 126
15. Calero P, Nikel PI (2018) Chasing bacterial chassis for metabolic engineering: a perspective review from classical to non-traditional microorganisms. Microb Biotechnol 12(1):98–124.
www.ncbi.nlm.nih.gov/pmc/articles/PMC6302729/. https://doi.org/10.1111/1751- 7915.13292
16. Beites T, Mendes MV (2015) Chassis optimization as a cornerstone for the application of synthetic biology based strategies in microbial secondary metabolism. Front Microbiol 6:9.
https://doi.org/10.3389/fmicb.2015.00906
17. Adams BL (2016) The next generation of synthetic biology chassis: moving synthetic biology from the laboratory to the eld. ACS Synth Biol 5(12):1328–1330. https://doi.org/10.1021/
acssynbio.6b00256
18. Ishino Y et al (2018) History of CRISPR-Cas from encounter with a mysterious repeated sequence to genome editing technology. J Bacteriol 200(7):10–1128. www.ncbi.nlm.nih.gov/
pubmed/29358495. https://doi.org/10.1128/JB.00580- 17
19. Jinek M etal (2012) A programmable dual-RNA-guided DNA endonuclease in adaptive bacte­rial immunity. Science 337(6096):816–821. https://doi.org/10.1126/science.1225829
20. Cong L et al (2013) Multiplex genome engineering using CRISPR/Cas systems. Science 339(6121):819–823. https://doi.org/10.1126/science.1231143
21. Han K etal (2017) Synergistic drug combinations for cancer identied in a CRISPR screen for pairwise genetic interactions. Nat Biotechnol 35(5):463–474. pubmed.ncbi.nlm.nih.
gov/28319085/. https://doi.org/10.1038/nbt.3834
22. Sun D etal (2022) Why 90% of clinical drug development fails and how to improve it? Acta Pharm Sin B 12:3049–3062. https://doi.org/10.1016/j.apsb.2022.02.002
23. Scannell JW, Bosley J (2016) When quality beats quantity: decision theory, drug discovery, and the reproducibility crisis. PLoS One 11(2):e0147215. https://doi.org/10.1371/journal.
pone.0147215
24. Fellmann C etal (2016) Cornerstones of CRISPR–Cas in drug discovery and therapy. Nat Rev Drug Discov 16(2):89–100. www.nature.com/articles/nrd.2016.238. https://doi.org/10.1038/
nrd.2016.238
49