To effectively treat an autoimmune neurodegenerative disorder like multiple sclerosis we must combat both the autoimmune response and the resulting damage to the nerve insulating layer, myelin. NeuroMuSceteer genetically modifies T cells to target disease-specific autoantibodies and autoreactive cells and to act as regulators instead of effectors, promoting patient immunotolerance. We also introduce two specialized molecular structures, one that identifies microRNA biomarkers in myelin cells and one that releases therapeutic microRNAs to induce myelin regeneration. In this page we detail all the mechanisms and design elements of NeuroMuSceteer and how each of them contributes to our end-goal; a holistic MS treatment.
Chimeric Autoantibody Receptor Design
Background
Multiple sclerosis (MS) is a disease characterised by inflammation, loss of myelin sheaths, and degeneration of axons in the
central nervous system 1. Recent studies have shown that B cells and antibodies play essential roles in MS pathogenesis. B cells
accumulate in CNS lesions 2 and ectopic B cell follicles in the meninges of MS patients 3, and their functions include:
antigen-presenting,
stimulating self-proliferation of T cells,
producing pro-inflammatory cytokines and chemokines,
producing soluble toxic factors,
contributing to abnormal lymphoid aggregates, and
acting as a reservoir for Epstein-Barr virus infection.
These actions may contribute to both relapses in MS and the progression of the disease 4.
Previously, studies have shown that B cell depletion halts the progression of autoimmune diseases, in systemic lupus erythematosus 5,
multiple sclerosis 6, and rheumatoid arthritis 7.
B cell depletion therapies, such as targeting CD20 or CD19, have also shown favourable treatment outcomes by stopping new lesions in
the CNS of patients with multiple sclerosis and exerting long-lasting effects on T cells 8.
Nonetheless, there are desirable B cell lineages that produce the anti-inflammatory cytokines IL-10 and IL-35, which regress the
pathophysiology of the disease 9. As a result, autoreactive B-cell death while preserving favourable B-cell populations has emerged
as an intriguing study area for immune treatment in autoimmune diseases. Depleting the B cell repertoire lowers blood antibody
levels, increasing the risk of hypogammaglobulinemia and infections.
Let us take two known monoclonal antibody examples that are widely used and commercially available. Anti-CD-38 plus anti-CD-20
as a pan-clonal B cell depletion therapy for autoimmune illness has shown:
poor response durability,
re-expansion of pre-existing autoantibody-producing B-cell clones 10,
insufficient eradication of B memory cells or plasma cells 11 (poor mAb distribution in secondary lymphoid tissue sites)
We chose engineered T cells because they can efficiently travel to the central nervous system and other (immunologically)
compartmentalised areas. Therapeutic T cells have shown responses in cancer patients who had previously failed anti-CD20 or
anti-CD38 therapy 10.
The extracellular domain of chimeric autoantibody receptors (CAAR) consists of autoantigen conformational epitopes that act
as bait to trap autoreactive B lymphocytes 12. The intracellular domain incorporates one or more T-cell stimulatory domains that
cause cytotoxic reactions, such as CD137 and CD3ζ. In a mouse model of pemphigus vulgaris, CAAR T cells that recognize Desmoglein
3 were successfully used to eliminate autoreactive B cells that cause the illness 13. Preclinical research showed positive outcomes
in treating pemphigus vulgaris 14 and myasthenia gravis 15.
Design workflow
In order to design our chimeric autoantibody receptor, we began by identifying all the sequences of interest (see below) and
gathering relevant sequences from databases such as NCBI, UniProt, and the iGEM Registry, while utilising PDB to analyse the
structure of individual domains. We then visualised and refined the structural models using PyMOL and conducted codon optimization
via Twist Bioscience to enhance expression. Sequence design and visualisation were performed on Benchling, then we used
Robetta-Baker Lab and its deep learning based modelling method, RoseTTAFold for structural modelling. The design process was
further informed by recent literature, including studies by Castella et al. (2019), Rafiq et al. (2020), Ellebrecht et al. (2020),
and Chang & Chen (2017), along with insights from two previous iGEM teams that developed CAR constructs (iGEM Patras med 2023,
iGEM Munich 2022).
The original NeuroMuSceteer CAAR construct consists of genes encoding a part of the myelin oligodendrocyte glycoprotein (amino acid 35-55),
the CD8 signal peptide, the CD8α hinge domain, the transmembrane region of the CD8 molecule, and an intracellular signalling domain
containing both CD137 and CD3ζ intracellular domains. The CAAR encoding gene was inserted into the C1 PGK vector downstream to the
BamHI cut site and upstream to the KpnI cut site.
The MBP-CAAR construct extracellular part consists of a gene encoding a part of the myelin basic peptide (amino acid 83–99),
while the rest of the domains and the vector were as previously described.
CAAR: Modular Assembly
Modularisation of chimeric autoantibody receptor proteins.
The concept of scalably creating chimeric proteins that will recognise a vast variety of autoantibodies, would be an innovative
step in the fight against autoimmune disease: both for the creation of multiple receptors per disease, and for the continuous
invention on a larger scale of new receptors against novel illnesses. The NeuroMuSceteer receptor serves as a proof of concept,
with the next step being scaling the project. This could be done in two ways, each with its benefits and drawbacks.
The first solution is the creation of a common genetic epitope using modular cloning, with three categories of genes:
E (extracellular), T (transmembrane), and S (signalling).
Category E are the variable extracellular domains, which include a
signal peptide and the extracellular epitope that binds to the autoantibodies of the disease. So, if Multiple Sclerosis is the
disease, and we have anti-MBP antibodies, the epitope of interest would be the part of MBP that the antibodies bind to.
Category T includes the transmembrane domains and the linkers. Certain selections from category T can introduce useful features
like homodimerisation of the receptors.
Category S is a collection of signalling or costimulatory domains that have been used in CAR and CAAR constructs before and induce
a variety of cell responses. This collection can be expanded in the future and the selection would be based on the desired cell
response. Responses induced by the costimulatory and signalling domains include proliferation, target cell death, cytokine
production.
Selection of Autoantibody-Binding Epitopes
Antigens in MS include myelin proteins like myelin basic protein (MBP), myelin oligodendrocyte glycoprotein (MOG), and
proteolipid protein. These proteins are characterised by their encephalitogenic segments, which can be analysed using a stepwise
reduction of complexity. Pacini et al. (2015), created an experimental autoimmune encephalomyelitis model (numerous studies
on multiple sclerosis are carried out using it) - by immunising C57BL/6 mice with the 21-mer immunodominant peptide representing
a partial sequence of MOG (35-55). They analysed the anti-MOG antibody response in this model using the recombinant refolded
extracellular domain of the protein, MOG (1–117), as well as five synthetic peptides mapping the 1–117 sequence of MOG (1-34,
35-55, 56-75, 76-95, 96-117) to assess the presence of a B-cell intramolecular epitope spreading mechanism. The results indicate
that although out of five, mostly MOG (35-55) is immunodominant, the recombinant, refolded MOG (1-117) may induce an even stronger
immunologic response.
MOG (35-55) also appears in Androutsou et al. (2018), where it is suggested that encephalitogenic T cells recognize MOG and its immunodominant
epitopes (epitopes 1-22, 35-55 and 92-106) as foreign antigens and cause the destruction of myelin, leading to multiple sclerosis.
MOG (35-55)’s potential role in the treatment of MS is further discussed in Androutsou et al.'s (2023) investigation of possible modifications
of the MOG (35–55) peptide during production and stability studies.
In summary, MOG (35-55) is the most reviewed MOG epitope in the literature investigating human antibody responses to various MOG peptides.
It displays a random coil formation.
Ellebrecht et al. (2016), testing a five-extracellular-cadherin-domain protein, Dsg3, as the CAAR extracellular autoantigen domain, provide a
robust justification as to why the MOG (35-55) peptide might be preferable to the recombinant refolded MOG (1-117), by explaining that
since T cell activation depends on the intermembrane distance of the immunologic synapse, shorter conformational fragments of the extracellular
autoantigen domain should enhance CAAR efficacy14. This is supported by Choudhuri K. et al. (2005), who discuss the binding of a T-cell antigen
receptor (TCR) to peptide antigens presented by major histocompatibility antigens (pMHC). Their research indicates that increasing the dimensions
of the TCR–pMHC interaction by elongating the pMHC ectodomain greatly reduces TCR triggering without affecting TCR–pMHC ligation.
The relevance of MBP 83-99 as an immunodominant myelin peptide in MS has been shown by numerous studies 1617. After Professor Mpoziki’s comments,
we switched our extracellular immunodominant epitope from only MOG to either MOG or MBP (83-99). The MOG-including model of our chimeric
protein, she argued, is indeed a good target in mice but ranks second as epitope of choice in humans (explanation needed).
Transmembrane and Intracellular Part Design
Linker Design
The linker region connects the autoantibody-binding domain to the transmembrane domain.
Our linker is based on the standard 15-mer (G4S)3 or 20-mer (G4S)4 design that many scFv-based CARs have. After an engineering cycle
[link], the design was slightly tweaked, reducing the serines to half (G4S)-(G5)-(G4S)-(G5). This was in attempt to stabilise the
spatial relationship between the transmembrane and extracellular domains, enhancing control over the domain orientation of the
small immunogenic MOG or MBP domain 1819.
Selection of the Transmembrane Domain
Function: This domain anchors the receptor in the cell membrane. Potential for dimerisation. Common choices are the transmembrane
regions from CD8a, CD28, or CD3ζ.
Function: As part of the TCR-CD3 complex present on the T-lymphocyte cell surface, it plays an essential role in adaptive immune
response. When antigen presenting cells activate the T-cell receptor (TCR), TCR-mediated signals are transmitted across the cell
membrane by the CD3 chains CD3D, CD3E, CD3G and CD3Z. All CD3 chains contain immunoreceptor tyrosine-based activation motifs
(ITAMs) in their cytoplasmic domain.
Function: As an integral membrane glycoprotein, it plays an essential role in the immune response and serves multiple functions
in responses against both external and internal offences. CD8A homodimer molecules also promote the survival and differentiation
of activated lymphocytes into memory CD8 T-cells.
Function: As another integral membrane glycoprotein, it also plays an essential role in the immune response and serves multiple
functions in responses against both external and internal offences. In T-cells, CD4 functions primarily as a coreceptor for MHC
class II molecule-peptide complexes. In other cells such as macrophages or NK cells, it works via differentiation/activation,
cytokine expression and cell migration in a TCR/LCK-independent pathway. It participates in the development of T-helper cells
in the thymus and triggers the differentiation of monocytes into functional mature macrophages.
Function: CD28 is a receptor that plays a role in T-cell activation, proliferation, survival and the maintenance of immune
homeostasis. It functions not only as an amplifier of TCR signals but delivers unique signals that control intracellular
biochemical events that alter the gene expression program of T-cells.
Function: ICOS enhances all basic T-cell responses to a foreign antigen, namely proliferation, secretion of lymphokines,
up-regulation of molecules that mediate cell-cell interaction, and effective help for antibody secretion by B-cells. It is
essential for both efficient interaction between T and B-cells, as well as normal antibody responses to T-cell dependent
antigens.
Selection of the Intracellular Signalling Domains
Function: These domains trigger T-cell activation upon antigen binding.
The most used signalling domains are from CD3ζ and costimulatory molecules like CD28 or 4-1BB (CD137).
Function: CD 28 is a receptor that plays a role in T-cell activation, proliferation, survival and the maintenance of immune
homeostasis. It functions not only as an amplifier of TCR signals but delivers unique signals that control intracellular
biochemical events that alter the gene expression program of T-cells.
Function: 4-1-BB is a receptor for TNFSF9/4-1BBL. It conveys a signal that enhances CD8+ T-cell survival, cytotoxicity, and
mitochondrial activity, thereby promoting immunity against viruses and tumours.
Function: OX40 is a receptor for TNFSF4/OX40L/GP34. It is a costimulatory molecule implicated in long-term T-cell immunity.
Function: ICOS enhances all basic T-cell responses to a foreign antigen, namely proliferation, secretion of lymphokines,
up-regulation of molecules that mediate cell-cell interaction, and effective help for antibody secretion by B-cells.
It is essential for both efficient interaction between T and B-cells and for normal antibody responses to T-cell dependent
antigens.
Function: CD27 is a costimulatory immune-checkpoint receptor expressed at the surface of T-cells, NK-cells and B-cells which
binds to and is activated by its ligand CD70/CD27L expressed by B-cells. The CD70-CD27 signalling pathway mediates antigen-specific
T-cell activation and expansion which in turn provides immune surveillance of B-cells.
Function: MYD88 is an adapter protein involved in the Toll-like receptor and IL-1 receptor signalling pathway in the innate immune response.
Function:Receptor on natural killer (NK) cells for HLA-C alleles. Does not inhibit the activity of NK cells.
Rafiq, S., Hackett, C.S. & Brentjens, R.J. Engineering strategies to overcome the current roadblocks in CAR T cell therapy. Nat Rev Clin Oncol 17, 147–167 (2020). https://doi.org/10.1038/s41571-019-0297-y
Vector Selection
We selected the C1 PGK plasmid after Professor Nikoletta Psatha’s recommendation, for its chromatin insulator and increased safety profile.
Chromatin insulators are DNA elements that regulate gene expression, preventing the spread of heterochromatin 32, and blocking
enhancer-promoter interactions, thereby preventing inappropriate gene activation 33. Chromatin insulators also improve the safety
of vector-mediated gene integration by creating a protective boundary around the inserted genes, preventing disruption or
dysregulation. This reduces the risk of adverse side effects and enhances the overall safety of gene therapy treatments 34.
Epigenetic induction of FOXP3 expression for T-cell to Treg Modification
Why FOXP3
T-cells, particularly autoreactive CD4+ T-cells of the Th1 and Th17 subtypes, play a crucial role in driving the autoimmune response in MS.
These T-cells infiltrate the CNS and release pro-inflammatory cytokines that exacerbate neuroinflammation, contributing to the destruction of
myelin and neuronal damage 35. Dysregulated T-cell activity is thus a central feature of MS pathogenesis.
Regulatory T cells (T-regs), which express the transcription factor FOXP3, are essential for maintaining immune tolerance and preventing excessive
immune responses. In MS, a reduced number or impaired function of FOXP3+ T-reg cells has been observed, leading to inadequate suppression of
autoreactive T-cells 36. Given the critical role of T-reg cells in modulating immune responses, enhancing their activity or restoring their
functionality has emerged as a potential therapeutic strategy in MS 37.
T-cell-based therapies have been explored for MS treatment, focusing on either limiting T-cell migration to the CNS or modulating their immune
activity. For instance, therapies like fingolimod and natalizumab prevent T-cells from entering the CNS, thereby reducing inflammation 38.
Despite their efficacy, these treatments often carry significant risks, such as increased susceptibility to infections. Furthermore, autologous
hematopoietic stem cell transplantation (AHSCT) has been investigated as a strategy to reset the immune system and induce immune tolerance in MS,
though it remains a high-risk procedure 3940.
In our project, we aim to transform K562 cell lines, which share key functional similarities with T-cells, into regulatory T cells (T-regs) using
CRISPR-dCAS9-VPR technology. This will be achieved by designing specific single-guide RNAs (sgRNAs) to target critical genes involved in T-cell regulation,
followed by the introduction of a chimeric auto-antibody receptor (CAAR) to further enhance T-reg cell functionality. By leveraging precise
gene-editing tools, this approach offers a novel strategy for modulating immune responses in MS, potentially providing a more targeted and safer
alternative to current therapies.
Cell Line Selection
As we mentioned above, CD4+ T-cells are known to infiltrate the CNS, releasing pro-inflammatory cytokines such as IFN-γ and IL-17, which drive
neuroinflammation and myelin destruction 41. Additionally, a dysregulation in the balance between effector T-cells and regulatory T cells (T-regs)
has been implicated in MS progression, highlighting the complexity of T-cell dynamics in autoimmune pathology 42.
However, the use of patient-derived T-cells in experimental studies presents several ethical and biological challenges. The collection of T-cells
from MS patients involves invasive procedures, and patient-derived cells can vary widely in their characteristics due to individual disease
variability, potentially confounding experimental results 43. Additionally, manipulating primary T-cells is technically challenging, with
limitations in gene editing efficiency, expansion, and culture viability. These factors prompted us to explore alternative cell lines that could
mimic T-cell function without the associated complexities of primary cell handling.
HEK293T cells, derived from human embryonic kidney cells, are a popular choice in gene-editing experiments due to their high transfection efficiency,
rapid growth, and ease of manipulation 44. Their use in CRISPR-based experiments allows for efficient testing of gene-editing strategies, making
them a valuable tool for proof-of-concept studies 45. However, their significant divergence from T-cell biology limits their utility in modelling
immune-specific processes such as T-cell activation and regulation. HEK293T cells lack the immune-relevant receptors and signalling pathways that
are critical for studying T-cell function, making them unsuitable for applications requiring accurate modelling of T-cell behavior 46.
Therefore, despite their experimental advantages, HEK293T cells were not selected for our project.
K562 cells, a myeloid leukemia cell line, were chosen for their functional similarity to T-cells, particularly in their expression of certain surface
markers and signalling pathways 47. Although they originate from a different lineage, K562 cells share key features that make them suitable for
studying immune modulation and T-cell-like behavior, including the ability to be genetically manipulated and expanded easily in culture. One
disadvantage of K562 cells is their cancerous origin, which can sometimes introduce variability in gene expression. However, their adaptability
to gene-editing techniques, combined with their ability to mimic certain T-cell functions, makes them an ideal platform for our experiments 48.
Following the advice of Mrs. Psatha, who leads the CRISPR-dCAS9-VPR aspect of the project, along with Mrs. Giannaki and Mrs. Papadopoulou, who emphasized
K562 cells' safety and easier handling, we opted for K562 as the cell line for our study.
Why CRISPR-dCAS9-VPR
Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) technology, coupled with the Cas9 nuclease, has revolutionized gene editing,
enabling precise modifications at specific genomic locations. CRISPR allows researchers to introduce targeted double-strand breaks in DNA, which are then
repaired by the cell’s natural mechanisms, leading to gene disruption or insertion of new genetic material 54. The versatility of CRISPR has broad
applications in various fields, including functional genomics, therapeutic development, and disease modeling 55. Its primary advantages include high
specificity, efficiency, and the ability to edit multiple genes simultaneously, making it a transformative tool in biomedical research 56.
CRISPR-dCAS9-VPR was selected as the most suitable tool for our project due to its precision, essential for editing the FOXP3
gene in K562 cells. Given that our objective is to transform K562 cells into regulatory T cells analogues (T-regs), accurate and efficient gene targeting
is crucial to ensure the desired modifications without introducing off-target effects 57. Traditional methods of gene editing, such as TALENs or ZFNs,
are more labor-intensive and less efficient when compared to CRISPR-dCAS9-VPR, which offers rapid sgRNA design and high success rates for gene knockout 58. This
makes CRISPR-dCAS9-VPR particularly advantageous for our experiments. As mentioned, we aim to introduce specific sgRNAs into K562 cells to mimic T-cell regulatory function
by altering FOXP3.
In our experimental design, the implementation of CRISPR-dCAS9-VPR follows several key steps. First, we design and clone the sgRNAs specific to the FOXP3 gene into
the pAW12.lentiguide.GFP plasmid, replacing the GFP cassette with our sgRNA sequences. Once the sgRNA-carrying plasmid is prepared, it is introduced into
K562 cells via a lentiviral vector, ensuring stable expression of the sgRNAs. After transfection, the Cas9 protein binds to the sgRNAs and is directed to
the FOXP3 gene, where it induces double-strand breaks, leading to gene modification. This step is followed by cell expansion and selection to ensure that
only successfully edited cells are used for further analysis. By using this method, we aim to generate a stable population of FOXP3-modified K562 cells,
which can then be assessed for their potential to exhibit T-reg cell-like functions.
Vector Selection
For this project, we required a plasmid capable of carrying the sgRNAs necessary for gene editing via CRISPR-dCAS9-VPR. Our approach involved selecting a plasmid in
which the green fluorescent protein (GFP) cassette could be removed and replaced with the designed sgRNAs using the BsmBI restriction enzyme. Once the
sgRNAs were inserted, the plasmid would be introduced into stable E. coli strains for amplification and production in large quantities. These amplified
plasmids would then be extracted and prepared for transfection into K562 cells using an appropriate delivery vector. After evaluating various options, we
selected the pAW12.lentiguide.GFP plasmid as the backbone for our experiment.
The pAW12.lentiguide.GFP plasmid was chosen for several reasons. It offers a lentiviral system that facilitates efficient gene delivery into both dividing
and non-dividing cells, making it ideal for experiments requiring stable transduction of sgRNAs into K562 cells 49. Additionally, its GFP cassette allows
for easy tracking and selection of successful transfections, though in our case, the GFP region would be replaced with the sgRNAs of interest. The plasmid’s design,
which includes sites for easy modification and insertion of sgRNAs, ensures its suitability for CRISPR-dCAS9-VPR applications. Moreover, its compatibility with BsmBI for
precise insertion and its high efficiency in cloning and expression in K562 cells make it a strong candidate for this project. Mrs. Psatha, who has extensive
experience with this plasmid in similar gene-editing experiments, proposed its use due to the familiarity of her team with its strengths and limitations. Her
knowledge ensures that any potential challenges can be navigated efficiently.
Single-guide RNAs (sgRNAs) play a critical role in CRISPR-based gene editing by guiding the Cas9 nuclease to specific genomic locations where double-strand breaks
are introduced. The sgRNA consists of a 20-nucleotide sequence that is complementary to the target DNA region, and it binds the Cas9 protein, directing it to the
site of interest. Once the Cas9-sgRNA complex binds to the target DNA, Cas9 creates a double-strand break, allowing for precise epigenome modifications via the cell's
DNA repair mechanisms 51. The accuracy of CRISPR-dCAS9-VPR depends largely on the design and selection of effective sgRNAs, which ensures specific targeting while minimizing
off-target effects 52.
To identify suitable sgRNAs for targeting the FOXP3 gene, we used the CRISPick tool 53, which is specifically designed for high throughput sgRNA selection based on
target gene specificity and predicted efficiency. From the FOXP3 gene, we selected 5 non-overlapping sgRNAs, which were designed to cover distinct regions of the
gene, minimizing the risk of off-target effects and ensuring effective gene disruption. After obtaining the sequences, we took their complementary strands and
oriented them correctly from 5' to 3'. Subsequently, we added restriction enzyme sites (BsmBI) to both ends of each oligo, generating 10 final guide RNAs for
insertion into the plasmid. This careful design process ensures efficient and precise gene editing, crucial for the success of our CRISPR-based transformation of
K562 cells.
Example of Oligos designing and introduction of BsmBI restriction sequences
Final FOXP3 Oligos
Input
No. Oligo
Final Oligos sequences
FOXP3
Oligo 1
CACCGAGAAGAAAAACCACGCTGTA
FOXP3
Oligo 2
AAACTACAGCGTGGTTTTTCTTCTC
FOXP3
Oligo 3
CACCGTATTAGAAGAGAGAGGTCTG
FOXP3
Oligo 4
AAACCAGACCTCTCTCTTCTAATAC
FOXP3
Oligo 5
CACCGCACACTCATCGAAAAAAATT
FOXP3
Oligo 6
AAACAATTTTTTTCGATGAGTGTGC
FOXP3
Oligo 7
CACCGTGCGCTGATAATCACGGGGT
FOXP3
Oligo 8
AAACACCCCGTGATTATCAGCGCAC
FOXP3
Oligo 9
CACCGATTGATACCTCTCACCTCTG
FOXP3
Oligo 10
AAACCAGAGGTGAGAGGTATCAATC
T cell Transformation
Transforming K562 cells into regulatory T cells (T-regs) is critical for developing innovative therapeutic approaches for autoimmune diseases like multiple sclerosis
(MS). T-regs play a vital role in maintaining immune homeostasis and preventing excessive inflammation by suppressing autoreactive T-cell activity 59. By
generating K562 cells that express key T-reg FOXP3 marker, we aim to create a stable cell line that can modulate immune responses effectively. This transformation
may facilitate the development of cell-based therapies that can restore immune balance in MS, providing a potential alternative to existing treatment modalities 60.
In our experimental design, we utilize the amplified pAW12.lentiguide.GFP plasmids containing our sgRNAs to allow for efficient transduction of K562 cells. This step
is critical for expressing FOXP3 in the K562 cells, as the lentiviral system facilitates stable integration of the gene into the host genome. The transfection process
involves introducing the lentiviral vector into the K562 cells, where it delivers the necessary genetic material to induce FOXP3 expression. Following transduction,
we can select successfully modified cells based on their expression of T-reg specific marker, enabling us to establish a robust cell line to use for our CAAR-T cell
experiments.
Despite the promising nature of this approach, several potential restrictions could impact the efficiency and success of the transformation. One significant challenge
is the low transfection efficiency associated with K562 cells 61, which can result in insufficient expression of FOXP3. To overcome this, we optimized the
transduction protocol by adjusting the multiplicity of infection (MOI) and employing lipofectamine as a transduction enhancer 62. This adjustment significantly
increased the efficiency of lentiviral transduction, allowing us to achieve a higher rate of successful FOXP3 expression in K562 cells. By addressing this challenge,
we aim to create a stable population of transformed K562 cells that can effectively function as T-regulatory cells.
Highly Specific microRNA Release Mechanism for Remyelination
Our mechanism is primarily based on Hybridization Chain Reaction (HCR), an isothermal and enzyme-free nucleic acid amplification
technique. It was introduced by Pierce et al. in 2004 and involves the initiation of a reaction by a single-stranded DNA initiator,
which triggers a series of hybridization events between two complementary DNA hairpins, forming a double helix polymer 63.
The design built upon the logic of our 2022 project, “Theriac”. It consists of two hairpin sets:
a set of HCR hairpins that executes the basic principle of the technique and releases the therapeutic microRNAs, and
a Y or T-structure that ensures specificity and enhances safety. It does so because the initiator strand for the HCR is part of the T structure and only gets released if the disease and cell-specific microRNAs are present in abundance.
Figure 1: Overview of the complete mechanism (HCR hairpins and T structure)
Specificity mechanism (T structure)
The T structure is comprised of three strands, T1, T2 and T3, functioning as follows:
The T1a strand is complementary to microRNA-125a-3p and has a few unpaired bases at the 3’ end that can readily bind to the 5’ end of the microRNA.
T2 is designed complementary to miR-146a-5p.
T3 is the sequence that results from the complementarity to T1 and T2, with an additional 2 unpaired bases that resulted from trial and error.
In abundance of microRNA-125a-3p, first T1a, then T1b thermodynamically unbind and the whole T1 strand is released, leaving unpaired
bases on the other two strands. If microRNA-146a-5p also exists in abundance, it binds and releases T2, its complementary strand,
and T3, the initiator for the hybridization process.
Figure 2. General overview of T structure function, initiator release and HCR triggering.
Specificity mechanism microRNA selection
The miR-125 family plays an important role in the nervous system, directing the differentiation of embryonic stem cells toward neurons
and neuroglia 6465. The 125a homolog and the -3p strand specifically, is more highly expressed in the CNS than any other tissue and
even more so in OLs and neurons. When overexpressed, it has been shown to impede progenitor maturation of oligodendrocyte lineage cells as
well as other critical processes for myelin formation such as OPC migration, Myelin Basic Protein production and integration. It binds and
regulates significant maturation genes like Gas7, Nod1, Slc8a3 and Smad4. miR-125a-3p was also detected in elevated amounts in the cerebrospinal
fluid of Multiple Sclerosis patients, indicating its outflow from neural cells undergoing degeneration 66. These findings are supported by
a follow-up study, confirming the results using mouse models , demonstrating the restorative effects of the molecule’s silencing in vivo and
ex vivo and further establishing its clinical relevance in the disease pathology 67.
This molecule is heavily implicated in neurodegeneration and inflammatory response, with its genetic polymorphisms and irregular expression
levels being linked to various CNS and autoimmune disorders 68. It has been demonstrated to impact oligodendroglia in diverse ways. Despite
being identified as a positive regulator of OPC differentiation to mature myelinating cells, its knock out yielded favourable results in terms
of remyelination and reduced neuroinflammation in cuprizone mouse models 6970. miR-146a is also a prominent biomarker from the very early
stages of Multiple Sclerosis, being elevated in the serum as well as the cerebrospinal fluid and brain lesions of patients. Further confirmation
came from its abnormally high levels in active brain lesions of patients compared to non-active brain tissue and the healthy control group 7172.
Release mechanism (HCR)
The HCR set consists of Hairpin H1, H2, H3, and H4. The hairpins are designed with specific domains, a, b, c, d, e and
their complementary domains, a*, b*, c*, d*, e*. Domain a and b are based on the initiator sequence, while the rest are
random and follow hairpin design considerations listed in the next section. The initiator is complementary to the 5' end
of the hairpin 1. When the initiator hybridises with H1, H1 unfolds and binds to the H2, which unfolds and attaches to H3,
which unfolds and binds to H4, which subsequently triggers the unfolding of H1, repeating the cycle. With each cycle involving
H1 through H4, the two therapeutic miRNAs, miR-219a-5p and miR-338-3p, are released.
Figure 3. Hairpin design and hybridisation chain reaction overview.
miR-219 is a major regulator of OPC differentiation to mature myelinating cells, inhibiting the expression of maturation suppressors like PDGFRα,
Sox6, FoxJ3, ZFP238 and Hes5 73. Its levels have also been shown to significantly decrease in multiple sclerosis lesions which validates not only
its endogenous function but its potential as a therapeutic agent as well 74. As indicated in various studies, miR-219 administration in demyelination
models has induced myelin sheath restoration thus improving disease severity and promoting recovery 757677.
Like miR-219, miR-338 targets differentiation inhibitors, modulates progenitor cell maturation and is greatly depleted in MS patient cells 78. The two
molecules operate jointly resulting in a deteriorated condition in their combined absence and therefore suggesting an enhanced therapeutic effect in their
combined use 79. Indeed, miR-219/ miR-338 transfection has been proven to increase the development of oligodendrocytes from precursor cells in vitro and
more importantly induce myelin regeneration in vivo 8081.
RNA mechanism Design Considerations
Selection of Identifier and Remyelinating microRNAs
We based the selection of target microRNAs on their implication in Multiple Sclerosis transcriptomics. We identified molecules that are reportedly overexpressed
in Multiple Sclerosis lesions, specifically in oligodendrocyte lineage cells and have a preventative role in myelin sheath formation.
The first step was to examine literature relating miRNAs to the disease and the demyelination/remyelination processes. miRs whose role or expression levels
were not linked to Multiple Sclerosis, were eliminated from the selection. Moreover, although some miRs were found highly expressed in patient serum -thus serving
as potential circulating biomarkers-, they lacked documentation regarding their presence in OLs and were also ruled out.
Next, the molecules were assessed with the use of relevant databases. Malacards is a database that details information about human diseases, including their
correlation to genes 82. Inputting the name of the miR gene in the search bar, provides a list of all diseases they are involved in. microRNA-146a was linked to 436
diseases amongst which were “Multiple Sclerosis”, “Primary Progressive Multiple Sclerosis”, “Relapsing-Remitting Multiple Sclerosis” and “Central Nervous System Disease”. mir125a
was a match for 269 diseases which included “Multiple Sclerosis”, “Relapsing-Remitting Multiple Sclerosis”, “Secondary Progressive Multiple Sclerosis”, “Demyelinating Disease”
and “Autoimmune Disease of the Central Nervous System”.
The miRs were then evaluated in the Expression Atlas, a database that visualizes experiment data to create the expression profile of a gene 83.
This analysis showed experiments conducted only in mice, with 5 out of 12 reporting significant expression levels of miR146a in the brain. mir125a was reported in 22
experiments all of which detected its presence in various regions of the brain.
The search was continued with another resource, the Genotype-Tissue Expression (GTEx) Portal which also depicts tissue-specific gene expression and the TissueAtlas,
a similar database specializing in small noncoding RNA 8485. Although the levels of the microRNA-146a transcript were relatively low in the brain, microRNA-125a was
strongly expressed in the brain and some other tissues like blood and skin.
Since the process produces the real therapeutic agents in the form of microRNAs, we made it a top priority to thoroughly investigate the available choices in order to ensure their
safety and efficacy. The ideal molecules should be downregulated in patients, have a sufficient safety profile with few to no off-target effects, and have a demonstrated regenerative
effect on oligodendrocytes—preferably on their maturation from OPCs, as that has been shown to be the key dysregulated stage in MS.
After a thorough review of the literature, miR-219 and miR-338 were immediately identified as the best options. They had already undergone testing as possible therapies,
in addition to being extensively studied for their function in OPC differentiation and remyelinating qualities.
Subsequently, we identified the genes these molecules target by employing miRTar and miRDB 8687. The former, is a manually curated database containing experimentally
verified information and the latter is a bioinformatic prediction tool that utilizes known miRNA-target interactions. The results of both resources for the two miRs served as
the data for Gene Set enrichment analyses on Reactome which displayed the most predominant participating pathways. This search revealed various stages and checkpoints of the cell cycle, cellular senescence and transcriptional modulation as the main procedures although it should be noted that a variety of pathways seemed implicated. Some examples are tumorigenesis regulation, neurotransmitter release and cytokine signaling.
Stem and toehold composition
The base pairs that close an RNA hairpin loop have a major impact on the loop's stability, completing the formation
of the double-stranded stem. The identities and arrangements of these closing pairs have been found essential for the
hairpin to remain structurally stable 88. G-C content should be kept under 30% in the toehold.
Loop size and composition
The stability of nucleic acid hairpins is strongly influenced by the loop size. Smaller loops are generally more stable due to
sufficient intraloop stacking interactions. On the contrary an increase in loop size reduces those interactions and is associated
with entropic penalties that result in instability. It should also be noted that loops shorter than three bases are sterically
constrained and unable to form, so stable loop length generally falls between 4 and 8 bases 89.
Thermodynamic parameters
Gibbs energy, or free energy, significantly impacts the stability of RNA hairpins, indicating whether a process requires external
energy or spontaneously. Predicting free energy changes is challenging, but computational models can improve thermodynamic
stability prediction 90. Check out the Model Page to find out more about such computational models we implemented in our design.
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