A binary self-amplifying expression platform enabling lipid nanoparticle-free vaccines and nanomedicines

Domain: biology
Published: 2025-12-22
Editorial outcome: major_revision

Abstract
Conventional mRNA vaccines played a crucial role in mitigating the COVID-19 pandemic but remain hampered by inherent instability, transient expression, limited payload capacity, and complex manufacturing, including their reliance on lipid nanoparticle (LNP) encapsulation. To address these challenges, this study describes the Gemini platform, an expression system with a bifunctional eukaryotic–prokaryotic promoter that can be deployed as either a self-amplifying RNA (saRNA) or as a self-amplifying DNA (saDNA) replicon, enabling robust amplification and expression of genetic cargo. Gemini eliminates the requirement for LNPs, exhibits enhanced stability during freeze–thaw cycles and lyophilization, and is compatible with ambient-temperature storage, thereby simplifying production and distribution. It maintains a strong safety profile, supports larger and more complex payloads than conventional mRNA vaccines, and induces prolonged protein expression, as demonstrated by a potent single-dose SARS-CoV-2 Gemini-based vaccine. With rapid, scalable manufacturing and flexibility across saRNA and saDNA formats, Gemini represents a versatile next-generation platform with potential for broad applications in molecular medicine and pandemic preparedness.

Introduction
Messenger RNA (mRNA) vaccines have demonstrated remarkable advantages in rapid development and adaptability1–7, yet they face significant challenges, including complex manufacturing requirements, thermal instability, reactogenicity, and limited payload capacity7,8. Notably, a major limitation is their reliance on lipid nanoparticles (LNP) for efficient mRNA delivery, which requires advanced technical infrastructure and raises concerns regarding long-term stability9. Moreover, these issues, together with rare adverse immune reactions10 and waning protection over time, highlight unresolved scientific hurdles in achieving durable and broadly protective vaccine immunity11. Consequently, there is a clear need for innovative platforms capable of achieving sterilizing immunity while overcoming these fundamental limitations.

Self-amplifying RNA (saRNA) delivery platforms present a promising alternative, overcoming many issues associated with conventional mRNA technologies. Recombinant saRNA expression vectors feature engineered replicons that encode and drive high levels of antigen expression12,13. Compared to mRNA technologies, significantly lower doses may be required, as tens of thousands of saRNA copies are synthesized, directing substantial mRNA transcription within recipient cells12. Moreover, saRNA vaccines can be delivered relatively non-invasively via intramuscular injection, similar to mRNA or DNA vaccines13,14.

Self-amplifying vaccines are considered safe and capable of inducing both humoral and cellular immunity while avoiding anti-vector immunity and minimizing the risk of vector genome integration into host genomes13,15. Compared to conventional vaccines, they offer lower intrinsic contamination risk from live infectious agents and improved scalability for mass production15. However, current saRNA vectors share several limitations common to established mRNA platforms: they require technically demanding in vitro transcription, their stability remains uncertain, and conventional paradigms suggest they are reliant on costly, specialized LNPs for cellular uptake and payload protein expression16, with LNPs themselves capable of inducing adverse effects1–3,10,17–19.

A critical consideration in LNP-based vaccine and therapeutic development is maintaining precise ratios between nucleic acid payloads and LNP formulations20–26. These ratios are essential for stability, encapsulation efficiency, and effective cellular uptake, and deviations can compromise formulation integrity, reducing efficacy or increasing toxicity. Additionally, LNP physical properties impose practical dosing volume limitations, as higher concentrations can promote aggregation or instability20–26. Administration restrictions, including maximum injectable volumes in preclinical models and human dosing guidelines, further limit the total deliverable dose and influence LNP-based therapeutic and vaccine design27.

Furthermore, the size of nucleic acid payloads that can be effectively incorporated into LNPs is inherently governed by several physicochemical and structural considerations. LNPs are optimized to encapsulate nucleic acids within particles of a defined size range, typically between 50-150 nm, to maintain stability, prevent aggregation, and ensure efficient cellular uptake18,21,28. Although mRNAs of ~1-2 kb are commonly employed and mRNAs up to ~4–5 kb can be incorporated effectively, longer sequences such as self-amplifying RNA (saRNA) ~9-10 kb or plasmid DNA >10 kb exhibit reduced encapsulation efficiency due to steric hindrance, increased viscosity, and weaker interactions with ionizable lipids, all of which are critical components for nanoparticle formation and subsequent endosomal escape9,15,21,29,30. Moreover, larger nucleic acids tend to produce more polydisperse LNP populations, decreasing particle stability, promoting aggregation, and altering biodistribution, ultimately compromising therapeutic performance21,24. These constraints necessitate careful optimization of LNP composition and nucleic acid length to balance encapsulation efficiency, stability, and in vivo efficacy, potentially requiring alternative delivery platforms for larger genetic payloads.

This study describes the Gemini recombinant expression system, a versatile bi-functional replicon platform capable of functioning as either a self-amplifying RNA (saRNA) or a self-amplifying DNA (saDNA). Gemini can be used with or without LNPs, allowing it to overcome key limitations of conventional vaccine platforms such as the need for LNP encapsulation, multiple dosing, and restricted payload capacity. Beyond vaccines, Gemini also holds broad potential for delivering and expressing recombinant proteins or nucleic acids in diverse nanomedicine applications.

Results
Both Gemini saRNA and saDNA induce amplification in transfected cells
The Gemini platform is a nucleic acid replicon-based, self-amplifying dual-expression vector (herein referred to simply as either saRNA or saDNA). It contains a prokaryotic T7 promoter that drives the in vitro transcription of mRNA to generate the saRNA system for delivery into cells or tissues. The platform also includes a eukaryotic promoter, the human cytomegalovirus immediate-early promoter/enhancer (CMV promoter), which functions in eukaryotic cells and drives transcription of saRNA from the saDNA version in cells or tissues (Fig. 1A, B). To validate the fidelity of the Gemini platform and its amplification capabilities, RT-PCR was used to measure the expression of negative-stranded mRNA in HEK293 cells transfected with either saRNA or saDNA (Fig. 1C). Notably, these transfection experiments were conducted without drug selection, demonstrating efficient uptake and expression. PCR products of the expected size were detected as nested PCR products from total RNA extracted from cells transfected with either saRNA or saDNA (Fig. 1D). The PCR products observed from the first round of PCR verifies that amplification occurred. To further ensure that the production of the negative-strand RNA was not due to primer-independent effects, no PCR products were found in either the initial PCR or subsequent nested PCR when the gene-specific forward primer was omitted during cDNA synthesis (Fig. 1D). This confirms the platform’s fidelity.

Both Gemini saRNA and saDNA drive protein expression in transfected cells
To validate Gemini’s ability to drive the expression of clinically relevant payloads, LNP-encapsulated Gemini constructs were initially used for direct comparison to mRNA vaccines, which are most often used in conjunction with LNPs. Subsequent experiments employed naked (non-encapsulated) Gemini constructs, as noted throughout the text.

To test Gemini’s ability to drive protein expression, HEK293 cells were initially transfected with either LNP-encapsulated saRNA (LNP-saRNA) or LNP-encapsulated saDNA (LNP-saDNA), both expressing the spike protein from the B.1.617.2 (Delta) variant of the SARS-CoV-2 virus. Transfection experiments were performed without drug selection to demonstrate the efficiency of uptake and expression (Fig. 2A). Western blot analysis 6 days post-transfection confirmed the presence of protein bands of the expected size (Fig. 2B, C). These results were corroborated by flow cytometry performed over a 6 day time course, tracking the expression of spike protein in transfected cells.

By day two post-transfection, weak spike protein expression was observed in HEK293 cells transfected with LNP-saDNA (6.06% of the total cell population). By day six, this positive fraction significantly increased to 26.0%, suggesting self-amplification of LNP-saDNA (Fig. 2D, E). Similarly, cells transfected with LNP-saRNA showed weak spike protein expression at day two (5.89% of the total cell population). By day six, the positive fraction increased to 33.2%, indicating the self-amplification behaviour of LNP-saRNA (Fig. 2D, E).

In contrast, cells transfected in a separate experiment with a conventional LNP-encapsulated pseudouridine-modified mRNA (LNP-mRNA) encoding the B.1.617.2 (Delta) spike protein initially showed 36.0% positivity for spike protein expression on day two. However, by day six, expression had rapidly waned, with only 6.08% of the cells remaining positive, which was a 6-fold reduction in expression (Fig. 2D, E) in vitro. The LNP-mRNA group experiment was performed separately from the saDNA and saRNA, allowing for only statistical comparisons within groups, however, the marked differences still demonstrate the short-lived expression of conventional mRNA in vitro.

Extended eGFP expression from LNP-encapsulated Gemini saDNA and saRNA in vitro
To compare the payload expression capabilities of the Gemini platforms in vitro, HEK293 cells were transfected with either LNP-saRNA or LNP-saDNA expressing eGFP (Fig. 3A). Western blot analysis confirmed protein expression, revealing a protein band of the expected size on day 6 post-transfection and sorting (Fig. 3B). Two days post-transfection, the cells were sorted to obtain 100% eGFP-positive cells. Flow cytometric analysis was performed weekly for up to 4 weeks to assess the duration of expression (Fig. 3D).

Cells transfected with LNP-saDNA were strongly positive for eGFP at day 14 (98%). By day 28, this positive fraction only slightly decreased to 93%, suggesting stable and long-term expression from the LNP-saDNA self-amplifying platform. In contrast, cells transfected with LNP-saRNA showed 85% positivity at day 14, but by day 28, this fraction significantly dropped to 64%, indicating less stability compared to LNP-saDNA. The difference in the fraction of positive cells between LNP-saDNA and LNP-saRNA was statistically significant at both 14- and 28-days post-transfection (Fig. 3E), with p-values of 0.0015 and 0.0025, respectively.

For comparison and in a separate experiment, cells transfected with conventional LNP-encapsulated pseudouridine-modified mRNA encoding eGFP initially exhibited high eGFP expression (93%) on day two post-transfection. However, by day six, there was a rapid decline in protein expression, as confirmed by Western blotting (Fig. 3C), and flow cytometry revealed an near three-fold reduction in eGFP-positive cells (28%) (Fig. 3D). Although comparison between groups is not possible because of these separate experiments, temporal comparisons within each group again demonstrate the short-lived expression of LNP-mRNA, as the p-value for the unpaired t-test between day two and day six was 0.0001 (Fig. 3E).

The Gemini platform expresses payload proteins for an extended period in vivo
To evaluate the dynamics of gene expression in vivo, mice were intramuscularly injected with LNP-saRNA or LNP-saDNA constructs encoding eGFP. eGFP expression was assessed at multiple time points (14-, 28-, and 42 days post-injection) by analyzing muscle tissue (Fig. 4A). This analysis included both qualitative (Fig. 4B) and semi-quantitative assessments (Fig. 4C, D). In these experiments, the Gemini constructs were delivered in a lipid nanoparticle associated form.

For LNP-saRNA, high eGFP levels were observed 14 days post-injection, which then diminished at later time points (28 and 42 days). The differences were statistically significant compared to the negative control, with p-values <0.05 for LNP-saRNA on day 14 and for LNP-DNA on day 42 (Fig. 4B, C). In contrast, LNP-saDNA exhibited a progressive increase in eGFP protein expression over time, peaking at 42 days post-injection (Fig. 4B, C). However, comparison of expression on day 14 post-injection showed that both LNP-saDNA and LNP-saRNA drove higher levels of eGFP expression than either LNP-plasmid DNA (pDNA) or LNP-mRNA, respectively.

Notably, eGFP expression from LNP-saDNA persisted robustly for up to 42 days, demonstrating a performance comparable to viral vector platforms, such as recombinant adenoviruses31 and vaccinia viruses32. Despite using a non-viral plasmid format, the self-amplifying saRNA technology in LNP-saDNA enabled long-term protein in vivo expression, lasting over 42 days. In contrast, LNP-saRNA appeared to be suited for applications requiring shorter protein expression durations, typically around 28 days. For example, LNP-saRNA could be used for transient protein therapies, such as short-term vaccination in prime–boost strategies or for driving the expression of proteins that promote tissue repair and regeneration, where prolonged expression is unnecessary.

In summary, both LNP-saRNA and LNP-saDNA constructs provided sustained eGFP expression, with LNP-saDNA demonstrating enhanced and prolonged activity. These findings underscore the potential of the Gemini platform for long-term therapeutic applications, offering significant advantages over conventional plasmid DNA (LNP-pDNA) and LNP-mRNA technologies.

Neither Gemini saRNA nor saDNA induces significant genomic integration
To assess the potential for genomic integration, 2-D gel-based methods were used to separate genomic DNA from extrachromosomal DNA33 and employed the properties of the restriction enzyme AscI to detect genomic integration in muscle tissue34. AscI cleaves DNA derived from prokaryotic cells but selectively ignores restriction sites that are CpG methylated in eukaryotic cells (Supplementary Fig. S6). An established agarose gel procedure, neutral-neutral 2D gel35,36, was utilized to distinguish between integrated and extrachromosomal nucleic acids to estimate the in vivo frequency of saRNA and saDNA integration in the genome of mouse muscle cells (Supplementary Fig. S7, Supplementary Table S1). While the saRNA format showed no detectable integration at the muscle injection site, the number of saDNA integrated copies was determined to be ~3.4×10-5 per cell genome. Such integration rate in muscle tissue is lower than that of plasmid DNA, (5×10-5)37, and adenoviruses, (6.7×10-5)38. As recombinant adenoviruses are widely used clinically and considered one of the safest vaccine vectors available38, this result demonstrates an excellent safety profile for saDNA and mitigates concerns about induced genetic abnormalities, such as those associated with lentiviruses and other commonly used retroviral expression systems (Supplementary Table S2). In conclusion, saRNA was demonstrated not to integrate into the host genome, while saDNA exhibited an integration frequency many orders of magnitude lower than the spontaneous somatic or germline mutation frequency observed in either mice or humans (Supplementary Table S1)39,40. These findings highlight the safety of the Gemini platform, with its integration rates well below thresholds associated with genomic risk, further emphasizing its potential for clinical use.

Stability of naked Gemini saDNA and saRNA to freeze-thaw cycles and lyophilization compared to conventional LNP-encapsulated mRNA vaccine
The stability of vaccine platforms is critical for determining their shelf life, distribution requirements, and overall efficacy. To evaluate the stability of the Gemini platform in comparison to conventional LNP-mRNA, each vaccine encoding the spike protein from the B.1.617.2 (Delta) variant of the SARS-CoV-2 virus was tested against freeze-thaw cycles and lyophilisation.

Freeze-thaw. All three platforms were subjected to multiple freeze-thaw cycles between +20 °C and -80 °C, followed by analysis via agarose gel electrophoresis. For the freeze-thaw stability test, 2 µg of naked saDNA and saRNA, and 1 µg of LNP-mRNA were used. The LNP-mRNA samples, which had been shipped on dry ice and stored at 4 °C overnight, were tested after being subjected to up to five freeze-thaw cycles, with each cycle involving freezing at -80 °C and thawing at +20 °C. Samples 1 through 5 represented increasing numbers of freeze-thaw cycles (ranging from two to five). Naked saDNA and saRNA samples were mixed with DNA or RNA loading dye and run on 1.2% agarose gels, while the LNP-mRNA samples were analyzed on 0.8% agarose gels to assess the stability of the large molecular weight LNP core structures (Fig. 5A).

Results indicate that both naked saDNA and saRNA maintained their structural integrity after five freeze-thaw cycles (Fig. 5B, C, E). In contrast, while the mRNA component of the LNP-mRNA remained intact, the LNP structure itself disintegrated after just a single freeze-thaw cycle, releasing free mRNA from the lipid nanoparticle core (Fig. 5D, F). This breakdown of the LNP likely results in the loss of the biological functionality typically provided by the encapsulation, thereby compromising the vaccine’s stability and efficacy.

Lyophilization. The stability of the three vaccine formats under freeze-drying (lyophilization) conditions was also assessed (Fig. 5G). Approximately 2.5 µg of each vaccine sample was freeze-dried in a total volume of 100 µL of Tris-Cl buffer, water, or PBS, using a Labconco FreeZone 4.5 L -105 C Complete Freeze Dryer System (720401000). The lyophilization parameters included solidification temperatures of -30 °C to -40 °C, pre-freeze temperatures of -40 °C to -50 °C, and a vacuum set point between 0.12 and 0.04. After freeze-drying, the samples were stored overnight at -20 °C and reconstituted the next day. These reconstituted samples were analyzed on 0.8% TAE-agarose gels alongside non-lyophilized controls to evaluate their structural integrity (Fig. 5H).

The results from the freeze-drying experiments further confirmed the superior stability of the naked saDNA and saRNA formats. Both platforms were successfully reconstituted after freeze-drying without any loss of integrity, whereas the LNP-mRNA formulation failed to remain stable. Upon reconstitution, the LNP-mRNA disassembled into free LNP and mRNA, reinforcing the limitations of LNP-mRNA formulations under such conditions.

Both Gemini platforms exhibit significantly greater stability compared to conventional LNP-mRNA vaccines under both freeze-thaw and freeze-drying conditions. While LNP-mRNA demonstrated vulnerability, breaking down after a single freeze-thaw cycle and disassembling after lyophilization, both naked saDNA and saRNA retained their nucleic acid integrity, making them more robust candidates for vaccine development and distribution, particularly in challenging environmental conditions.

Dose selection for LNP-encapsulated and naked vaccine formulations
The selection of the optimal dose for the LNP-encapsulated Gemini-D and Gemini-R vaccines was guided by a comprehensive review of published literature on LNP-mRNA SARS-CoV-2 vaccines. Prior studies have evaluated dose ranges between 0.01 µg and 10 µg, with higher doses generally correlating with enhanced immunogenicity. However, the difference in efficacy between 2 µg and 10 µg was not statistically significant41, indicating that a dose within this range would be sufficient to elicit a robust immune response.

Additional constraints influenced the dose selection, including the fixed nucleic acid-to-LNP ratio (2.5:1) required for formulation stability and the maximum allowable injection volume (25 µL per mouse) set by institutional animal care guidelines. Given these factors, 5 µg was determined to be the most suitable dose, which was confirmed in a dose titration study (Fig. 6B). Although this dose balances immunogenicity with formulation and administration limitations, these physiochemical and logistical constraints highlight critical yet often underappreciated factors in the development of LNP-based vaccines and immunotherapies.

To determine the optimal dose for naked (non-LNP) vaccines, a systematic dose titration study was performed (Fig. 6A, C). Various concentrations were tested, leading to the selection of 100 µg of naked saDNA and 25 µg of naked saRNA for the Gemini platform (Fig. 6C). These values were not arbitrarily chosen to favour naked formulations over LNP-encapsulated vaccines, but rather empirically derived based on immunogenicity data. This approach ensures that the selected doses were appropriate for subsequent comparative analyses between LNP-based and naked self-amplifying vaccine formulations, highlighting how both formulation and dosing strategies critically shape vaccine efficacy (Fig. 6).

Comparison of immune responses between different vaccine formulations
To evaluate the immune responses induced by various vaccine formulations, single dose titrations were performed to determine the optimal dose that elicited the maximal response. These doses were subsequently used to compare the immune responses of naked saDNA and saRNA formats with those of LNP-mRNA vaccines.

First, the short-term cytokine expression by injecting animals intramuscularly and sacrificing them at 2-, 4-, and 6 h post-inoculation was examined. Muscle tissue from the injection site and serum samples were collected for analysis (Fig. 6D). Results indicated that the saDNA group elicited a robust cytokine response, with levels continuing to increase up to the 6-h mark, suggesting a sustained immune response over time. In comparison, the saRNA group exhibited a non-inflammatory, immune-modulating cytokine profile. The mRNA group showed the lowest cytokine levels, while the saDNA group demonstrated the strongest overall response, potentially increasing further with time (Fig. 6E–L). This pattern was consistent with the antibody and T-cell responses observed in subsequent assays.

LNP encapsulation is not required to achieve potent immunogenicity from Gemini saDNA or saRNA vaccines
Current RNA vaccine platforms generally rely on lipid nanoparticle (LNP) encapsulation to protect mRNA or saRNA from RNAse digestion, which adds complexity and cost to the manufacturing process19. Previous studies have demonstrated that LNP encapsulation is necessary for inducing an equivalent antibody response, as shown with the HIV-1 Env gp140 protein model antigen23,40. In contrast, the goal here was to determine whether LNP encapsulation is essential for the immunogenicity of Gemini saDNA and saRNA vaccines using eGFP as a model antigen.

To assess this, the antibody responses of naked and LNP-encapsulated versions of the Gemini formats expressing eGFP in K18-hACE2 transgenic mice was compared (Fig. 7A). A higher dose of naked saDNA (50 µg) outperformed 5 µg of LNP-saDNA in inducing antibody responses (p=0.0105 vs. p=0.4038; Fig. 7B). Similar trends were observed for naked saRNA (p=0.0420) compared to LNP-saRNA (p=0.3270) (Fig. 7C). This indicates that higher doses of naked formulations can generate strong immune responses to eGFP comparable to, or even exceeding, those of lower-dose LNP-encapsulated versions.

We extended our studies by analysing IgG responses in mouse serum 28 days post-injection while comparing naked and LNP-encapsulated formulations of Gemini saDNA, saRNA, with benchmark LNP-mRNA vaccines, all encoding Omicron Spike. Across all comparisons, the naked saDNA group stood out, producing a significantly higher IgG response (p=0.0006). Although naked-saRNA (0.0084) and LNP-mRNA vaccines (0.0125) also showed significantly higher responses than the control, their responses were numerically lower than the naked saDNA (Fig. 7D). While comparing the LNP versions of Gemini vaccines, again the LNP-saDNA group stood out (p=0.0028) (Fig. 7E). These results were further supported by cytokine analysis, where the IFN-γ ELISPOT response indicated a stronger T cell response in the naked saDNA group (p=0.0010) compared to the other vaccine formats (Fig. 7F, G).

Both LNP-encapsulated and naked formulations of Gemini saRNA performed similarly in eliciting IL-4 and TNF-α ELISPOT responses (Fig. 7H–K). This suggests that LNP encapsulation may not be necessary for eliciting robust immune responses with Gemini vaccines and higher doses of the naked versions can compensate for the absence of encapsulation.

In conclusion, maximal T cell responses was achieved through vaccination with naked or LNP-encapsulated Gemini saDNA and saRNA formats, demonstrating that the naked Gemini vaccines can achieve comparable immunogenicity with appropriate dosing. These findings highlight the potential for simplifying vaccine manufacturing by omitting LNP encapsulation without compromising immunogenicity.

Significant antibody response induced by both Gemini SARS-CoV-2 spike naked saRNA and naked saDNA vaccine formats
To assess the type of antibody response induced, K18-hACE2 transgenic mice, which express the human ACE2 receptor for SARS-CoV-2, were injected with saRNA or saDNA vectors encoding the B.1.617.2 (Delta) spike variant of the SARS-CoV-2 virus (Fig. 8A). A 5 µg dose of each LNP-encapsulated vaccine formulation or a 50 ug dose of each naked vaccine formulation was administered.

In line with flow cytometry data, the IgG response in serum from mice vaccinated with naked saDNA on day 28 was significantly greater than in the unvaccinated control group (p=0.0046; Fig. 8B). Although the IgG response to the naked saRNA vaccine was lower than naked saDNA, it still remained higher than the unvaccinated group (p=0.1019). Conversely, the IgM response exhibited the opposite trend, with significantly higher levels generated by the naked saRNA format (p=0.0429) compared to the control group (Fig. 8C). In contrast, the naked saDNA vaccine produced a much lower IgM response and was not elevated (p>0.9999) when compared to the control group (Fig. 8C). Neither vaccine format induced a significant IgA response, and no observable toxicity such as weight loss was detected (p>0.05, data not shown).

While absolute quantitative estimates of antibody responses are scarce in clinical literature, a few studies38,42 provide relevant comparisons43,44. These studies, which tested thousands of patients, support the findings that LNP-saRNA and LNP-saDNA formats elicit strong antibody responses. Quantitatively, both LNP-saRNA and LNP-saDNA formats produced significantly higher IgG concentrations (400−800 ng/mL) after a single 5 µg dose, compared to the ~200 ng/mL observed in patients recovering from SARS-CoV-2 infections42.

In conclusion, the Gemini saRNA format may offer advantages in vaccine applications where IgM plays a critical role, while Gemini saDNA appears more effective for eliciting strong IgG responses. These differences could be attributed to the distinct Toll-like receptor (TLR) signalling pathways activated by RNA and DNA45, suggesting that the two Gemini formats provide the flexibility to fine-tune immune responses, depending on the desired antibody profile, either IgG or IgM dominant.

Durability of antibody responses induced by naked saDNA and saRNA vaccines
To evaluate the duration of antibody responses elicited by naked saDNA versus saRNA vaccines, a time-course study was conducted (Fig. 8D). Results showed that naked saRNA vaccines induced durable antibody responses for up to 42 days before a noticeable decline (Fig. 8E). In contrast, naked saDNA vaccines maintained robust antibody responses for at least 70 days before beginning to wane (Fig. 8E). Therefore, naked saDNA vaccines demonstrated a longer lasting and more durable antibody response compared to naked saRNA vaccines and were selected for subsequent viral challenge experiments.

Neutralizing antibody response to SARS-CoV-2 pseudo typed virus
Significant neutralization antibody titers were measured (Fig. 8F) using the SARS-CoV-2 pseudotyped virus titration assay, with similar levels observed between naked saDNA and naked saRNA vaccines (Fig. 8G), as normalized to saline control. This data underscores that naked vaccines induce high-titer antibody responses, trigger cytokine responses, and generate durable, long-lasting immunity.

Effectiveness of naked saDNA in reducing viraemia post-challenge
To assess whether naked saDNA vaccines could outperform LNP-encapsulated saDNA and potentially eliminate the need for LNP delivery systems, a viral challenge experiment was conducted using Delta SARS-CoV-2 and compared the protection given by LNP-encapsulated and naked Omicron-Spike saDNA vaccines. Mice were vaccinated intramuscularly with either LNP-encapsulated or naked saDNA on days 0 and 28. After a 5 day interval following the second dose, the mice were challenged with SARS-CoV-2 and euthanized 5 days post-challenge. Blood samples were analyzed for viraemia levels, focusing on nucleocapsid protein concentration (Fig. 9A).

A statistically significant reduction in nucleocapsid protein levels was observed in the serum of mice vaccinated with naked saDNA compared to unvaccinated controls, as determined by an unpaired t-test (p=0.0041) (Fig. 9B). In comparison, the LNP-saDNA group also showed a significant difference from the control group (p=0.0230) (Fig. 9C). This study underscore the importance of reduced viraemia, which is closely associated with the severity of COVID-19 and serves as a key indicator of vaccine efficacy. Demonstrating a significant reduction in viraemia supports the potential of naked saDNA vaccines in advancing towards effective sterilizing vaccines.

Methods
Mice and ethical approval
K18-hACE2 transgenic mice were (Jackson Laboratory, 034860) maintained in the Centre for Disease Modelling at the University of British Columbia (UBC). These experiments were approved by the Animal Care Committee at UBC, who is responsible for ensuring that all UBC animal researchers conform to the mandatory guidelines of the Canadian Council on Animal Care. The mice challenged with SARS-CoV-2 were maintained at the Toronto High Containment Facility level 3 (THCF) at the University of Toronto. These experiments were approved by the Animal Care Committee (University of Toronto), and also maintained and euthanized under humane conditions in accordance with the guidelines of the Canadian Council on Animal Care. Mice were maintained under 12 hr light/dark cycles at 20 °C ambient temperature.

Vector synthesis and preparation of saDNA and saRNA
Fig. 1A illustrates the map of the vector system discussed in this paper, hereinafter referred to as Gemini 1.0. It is based on the T7-VEE-GFP plasmid, a generous gift from Professor Steven Dowdy, at the University of California, San Diego School of Medicine,12. The vector consists of the NSP1-4 genes from the Venezuelan equine encephalitis (VEE) virus, an origin of replication site, a bacterial promoter (26S subgenomic promoter), an Ampicillin resistance (AmpR) gene acting as a selection marker for bacterial culture, a T7 promoter to recruit T7 RNA polymerase for saRNA synthesis, and a human CMV enhancer/promoter, allowing its use as a DNA or RNA vector in humans. The CMV promoter was subsequently cloned into the T7-VEE-GFP plasmid by Synbio Technologies. For the B.1.1.529 (Omicron) Spike variant of SARS CoV-2 and B.1.617.2 (Delta) spike variant of the SARS-CoV-2 virus and eGFP sequences (see Supplementary Fig. S1–5).

The Gemini 1.0 vector was transformed into DH5α Competent E. Coli (NEB, C2987), and plated onto Luria-Bertani (LB) agar containing Ampicillin for selection; this was followed by overnight culturing in LB broth at 37 °C. Vector DNA was extracted according to the EZ10 Plasmid DNA Minipreps Kit protocol (BioBasic, BS6149). This constituted the naked saDNA version of the Gemini 1.0 platform. To prepare the naked saRNA version, the Gemini 1.0 vector underwent in vitro transcription using T7 RNA polymerase (NEB, M0251L), followed by in vitro 5’ capping and 3’ polyadenylation. Figure 1 describes the self-amplifying platform pathways and in vitro replication process for both the DNA and RNA forms.

mRNA preparation
Pseudouridine substitute LNP-encapsulated mRNAs encoding eGFP (PM-LNP-21) or LNP-B.1.617.2 (Delta) spike protein variant of the SARS-CoV-2 virus (PM-LNP-12) mRNA were purchased from Promab Biotechnologies (Richmond, CA, United States). These LNP’s were formulated by Prolab with SM-102, DSPC, cholesterol, and DMG-PEG2000 at optimal molar concentration for a high rate of encapsulation and efficient mRNA delivery.

The conventional plasmid (pDNA) was either pCMV-T7-EGFP (addgene, plasmid 133962) or pCMV-Spike (addgene, plasmid 173921).

Lipid nanoparticles (LNP) formulation of Gemini saDNA and saRNA formats
The 5 µg dose of Gemini saDNA and saRNA was selected based on a thorough review of published literature on LNP-mRNA SARS-CoV-2 vaccines. Previous studies have utilized doses ranging from 0.01 µg to 10 µg, with higher doses generally yielding better immunogenicity. However, the difference in efficacy between 2 µg and 10 µg was not statistically significant, suggesting that a dose within this range would be optimal. Additionally, the formulation required a fixed nucleic acid-to-LNP ratio of 2.5:1, which further constrained the selection of an appropriate dose, with 5 µg being the maximum feasible concentration. Moreover, animal facility guidelines imposed a strict maximum injection volume of 25 µL per mouse, limiting the total amount of vaccine that could be administered. Considering these factors, a 5 µg dose was determined to be the most appropriate for the LNP-based vaccine formulations. These constraints represent an often-underappreciated aspect of all LNP-encapsulated vaccines and immunotherapies23.

The Encapsula GEN-7036 formulation, which contains a permanently charged cationic lipid (DOTAP-based), was chosen because it does not require a confined impinging jet (CIJ) turbulent mixer like Moderna Spikevax (mRNA-1273)1,2 and Pfizer–BioNTech’s Comirnaty (BNT162b2)3, and other vaccine formulations use. Instead, it can be mixed with nucleic acids at room temperature, and be freshly prepared just prior to injection. Unlike traditional LNPs that encapsulate nucleic acids within their core, permanently cationic formulations such as GEN-7036 primarily associate the nucleic acids on the particle surface. Furthermore, in preliminary head-to-head comparisons, the Encapsula GEN-7036 formulation produced higher antibody levels than the mRNA-1273-like ionizable SM-102 lipid nanoparticle formulation of the same vaccine and dose prepared using CIJ by the CDMO (Ardena Group Ltd.) (manuscript in preparation). Thus, LNP-encapsulated forms of Gemini saDNA and saRNA were prepared by mixing 5 µg of saDNA or saRNA with 18 µL of Genesome lipid solution (DOTAP:Chol:DOPE in a 1:0.75:0.5 ratio; Encapsula NanoScience, GEN-7036) in a 1:2 volume ratio at room temperature as described by the manufacturer. LNP-encapsulated nucleic acids were kept on ice until ready for injection.

LNP-mRNA preparation
Pseudouridine substitute LNP-encapsulated mRNAs encoding eGFP (Promab Biotechnologies, PM-LNP-21) or LNP-B.1.617.2 (Delta) spike protein variant of the SARS-CoV-2 virus (Promab Biotechnologies, PM-LNP-12) mRNA. These LNP’s were formulated by Promab Biotechnologies with SM-102, DSPC, cholesterol, and DMG-PEG2000 at optimal molar concentrations for a high rate of encapsulation and efficient mRNA delivery.

HEK293 cell culture and transfection with Gemini
HEK293 cells (ATCC; CRL-1573) were cultured in Dulbecco’s Modified Eagle Medium (DMEM; Gibco, 11965-092) containing 10% Fetal Bovine Serum (FBS; Gibco, A3160702) and 1:100 dilution of penicillin/streptomycin solution (Thermo Fisher Scientific, 15140122). Cells were seeded at a density of 5×105 cells per well in a 6-well plate 1 day prior to transfection. Transfection was performed with ~2.5 µg of either Gemini saDNA or saRNA using the Lipofectamine™ 3000 protocol (Thermo Fisher Scientific, L3000001) and was carried out without drug selection to either kanamycin or puromycin resistance encoded by the Gemini 1.0 vector.

Negative (-) strand mRNA detection
HEK293 cells were harvested 72 h post-transfection. Total RNA was extracted using the PureLink™ RNA Mini Kit (Ambion, 12183025), and its integrity was checked on a 0.8% agarose gel. Molecular weight marker used was 1 Kb Plus DNA Ladder (Froggabio, DM015. Thereafter, total RNA was treated with amplification grade DNase I (Invitrogen, 18068015) to remove any residual DNA, followed by first strand cDNA synthesis using either a NSP4 gene-specific forward primer with a random nucleotide tag sequence (5’-cggtcatggtggcgaataaGCGGCCTTTAATGTGGAATG-3) or without any primer according to the SuperScript™ III Reverse Transcriptase protocol (Invitrogen, 18080044). cDNA synthesis was then completed followed by a PCR using an eGFP gene-specific reverse primer (5’-CACCTTGATGCCGTTCTTCT-3’) and the random nucleotide tag-specific forward primer (5’-cggtcatggtggcgaataa-3’) to produce a 1.9 kb band which would be an indication of negative RNA strand. A nested PCR using the forward primer, 5’-CCGAGAGCTGGTTAGGAGATTA-3’, and reverse primer, 5’-GCTTGTCGGCCATGATATAGA-3’ on the first PCR product was then performed to amplify cDNA with a band size of 1.4 kb to verify the correct target sequence (see Fig. 1C). PCRs were run on a Bio-Rad T100 Thermocycler and parameters used for both PCRs were: 94 °C for 30 s, 56 °C for 30 s, 72 °C for 30 s, for 28 cycles.

Flow cytometry sample preparation
HEK293 cells were transfected with either: a) Gemini saDNA expressing SARS-CoV-2 spike protein, or b) a non-self-amplifying DNA plasmid control expressing SARS-CoV-2 spike, or c) LNP-B.1.617.2 (Delta) spike protein variant of the SARS-CoV-2 virus mRNA, or d) the conventional LNP-encapsulated Pseudouridine substitute mRNAs encoding the B.1.617.2 (Delta) spike protein variant of the SARS-CoV-2 virus, (see Fig. 2 for method overview). Cells were harvested at 2- and 6 days post-transfection as were the FACS samples and resuspended in FACS buffer at a concentration of 1.0×106 cells/mL. Subsequently, cells were incubated in FACS buffer for 30 min at 4 °C for Fc blocking, centrifuged (240xg for 4 min at 4 °C), and then stained with an anti-receptor-binding domain (RBD) SARS-CoV-2 spike antibody conjugated to Alexa Fluor 647 (1:100; Invitrogen, 51-6490-82) for 30 min at 4 °C in the dark. Cells were then washed in FACS buffer by centrifuging at 240xg for 4 min at 4 °C) and resuspended in FACS buffer (500 uL/tube). Data was acquired using a BD Cytoflex flow cytometer.

Fluorescence-activated cell sorting (FACS) sample preparation
HEK293 cells were transfected with either: a) Gemini saDNA expressing eGFP, or b) Gemini saRNA expressing eGFP, or c) LNP-encapsulated pseudouridine-substituted mRNAs encoding eGFP (Promab Biotechnologies, PM-LNP-21). Two days post-transfection, cells were sorted for eGFP expression. Cells were then harvested at 14- and 28 days post-transfection using Cellstripper® (Corning, 25-056-CI), and counted using a TC20 Automated Cell Counter (Bio-Rad, 1450102), assessing live cells with a 1:1 dilution with 0.4% Trypan Blue (Gibco, 15250-061). Cells were then resuspended in FACS buffer (1X phosphate buffered saline (PBS) with 2% FBS and 2% normal rabbit serum) at a concentration of 1.0×106 cells/mL and incubated in FACS buffer for 30 min at 4 °C for Fc receptor blocking. Blocked cells were again centrifuged at 240xg for 4 min at 4 °C, and resuspended in FACS buffer (500 µL/tube).

Western blot
HEK293 cells were transfected with either: (a) Gemini saDNA or saRNA expressing the SARS-CoV-2 spike, or (b) Gemini saDNA or LNP-encapsulated pseudouridine-substituted mRNAs encoding eGFP (Promab Biotechnologies, PM-LNP-21), or (c) LNP-encapsulated mRNA encoding the B.1.617.2 (Delta) spike variant of SARS-CoV-2 (Promab Biotechnologies, PM-LNP-12). Cells were harvested 72 h post-transfection, lysed in 2X sample buffer supplemented with 5% β-Mercaptoethanol (BME; Bio-Rad, 1610710), and heated at 90 °C for 10 min. Subsequently, samples were treated with Benzonase nuclease (Sigma, E1014) for 3 h to remove nucleic acids. A total of 30 µg of protein per well was loaded onto a 4-15% precast SDS-PAGE gel (Bio-Rad, 4561083). SDS-PAGE gels were run on the Bio-Rad Mini-PROTEAN® Tetra Vertical Electrophoresis Cell and the running conditions were as follows: 75 V for 20 min, then 120 V for 2 h, in running buffer (100 mM Tris, 100 mM Tricine, 0.1% SDS). Molecular weight marker used was BLUelf Prestained Protein Ladder (Froggabio, PM008). For Western blot, protein was transferred to a nitrocellulose membrane using the Bio-Rad Trans-Blot® Cell at 75 V for 3 h in Towbin buffer (2.5 mM Tris, 19.2 mM glycine, 2% (v/v) methanol). Subsequently, the membrane was washed in 0.1% Tween-20 in PBS (PBST), followed by blocking with 5% skim milk in 1% PBST for 2 h. Primary antibodies for ALFA Tag (Nano-tech, N1581) and eGFP (Thermo Fisher Scientific, GFP-101AP) were diluted 1:5000 and incubated with the membrane at 4 °C overnight. The membrane was then washed three times for 10 min each with 0.1% PBST. Anti-rabbit (Thermo Fisher Scientific, 31460) and anti-mouse (Abcam, AB205719) secondary antibodies conjugated to horseradish peroxidase (HRP) were diluted 1:5000 and incubated with the membrane at room temperature for 1 h, followed by three 10 min washes of 0.1% PBST. Subsequent signal detection was conducted on a ChemiDoc MP Imaging System (Bio-Rad).

Qualitative determination of eGFP expression in injected mouse leg muscles
Two groups of nine 6–12 week-old K18-hACE2 mice were injected with 5 µg of either LNP-saRNA or LNP-saDNA expressing eGFP, by intramuscular injection into the caudal thigh muscle. For each group, mice were sacrificed, at 14, 28 or 42 days post-injection (n=3 per day of sacrifice). Three mice injected only with saline were used as background controls and sacrificed on day 2 (n=3). Thigh muscles were excised and immediately frozen on dry ice in Epredia™ Neg-50™ frozen section medium (Fisher Scientific, 36-101-4314). Samples were stored at -80 °C until sectioned using a cryostat microtome and counter-stained with DAPI at The Centre for Phenogenomics (TCP), University of Toronto. Images were captured at the TCP facility (Fig. 4) and were subsequently assessed for qualitative expression of native eGFP. For each sample, four sectioned layers per sample were assessed, and the one with highest eGFP intensity was chosen per sample. A visual average was ascertained from these images for each time point and a suitable representative image was selected (Fig. 4B).

The highest eGFP intensity images were used to quantify eGFP mean intensity (Fig. 4C, D), utilizing ImageJ software to calculate mean intensity and total area for each sample. Weighted mean intensities were calculated for each vaccine group per time point, as the sum of the individual weighted mean eGFP intensities per sample. The individual weighted means were calculated using the following equation: (area sample / total area per time point) × mean intensity sample.

Immunization of mice
Groups of 15 week-old K18-hACE2 transgenic mice (Jackson Laboratory, 034860) were immunized with 5 µg of LNP-encapsulated or 50 µg naked saDNA or saRNA formats expressing the B.1.617.2 (Delta) spike protein variant of the SARS-CoV-2 virus or eGFP, or 50 µg naked saDNA or saRNA formats expressing the B.1.1.529 (Omicron) spike variant of the SARS-CoV-2 vaccine (see Supplementary Fig. S1 for the sequence). Optimal doses were determined in prior experiments utilizing other Spike constructs (Fig. 6B, C). Mice were immunized by intramuscular injection into the right caudal thigh muscle. Blood samples were taken from the left lateral saphenous vein before vaccination at day 1, and day 28 or day 42 post-initial vaccination. During the study, mice were monitored weekly (or more frequently if needed after injections or blood collection) for any behavioural changes or changes to body condition or weight. A humane endpoint was determined as a 20% overall weight loss or 10% weight loss from previous weight.

Cytokine bead-based array
Blood from mice was collected in 500 µL serum microvette tubes (Sarstedt, 20.1343.100) and centrifuged at 2000xg for 10 min at 4 °C. Serum was transferred to a fresh 500 µL microtube. Both leg muscles were collected, cut into small pieces with scissors, then incubated in 1 mL of Pierce™ RIPA Lysis Buffer (Thermofisher, PI89900) for 20 min at 4 °C. The sheared tissue was then sonicated with titanium beads for 20 min and centrifuged at 10,000xg for 10 min at 4 °C. Supernatant was transferred to a fresh 5 mL macrotube. Serum and leg muscle supernatants were mixed with 100X Halt™ Protease and Phosphatase Inhibitor Cocktail (Thermofisher, 78443) and 100X Penicillin-Streptomycin Solution (Thermofisher, 15140122), and stored at –70 °C prior to analysis.

The BD™ Cytometric Bead Array (CBA) Mouse Th1/Th2/Th17 CBA Kit (BD Biosciences, 560485) was used to determine cytokine concentrations from the serum and leg muscle supernatants. The protocol provided in the kit was followed. Samples were run on a Beckman Coulter CytoFLEX Flow Cytometer. Data was analyzed using CBA Analysis Software (V1.1.15) and visualized using GraphPad Prism (V10.1.1).

ELISA Protocols
All ELISA assays followed the same general workflow with antigen-specific variations noted below. Coating antigens or antibodies were diluted in coating buffer (0.1 M Carbonate, pH 9.5) and coated onto 96-well plates (Corning, 3369) overnight at 4 °C. Plates were washed four times with washing buffer (0.1% Tween-20 in 1X PBS), then blocked with blocking buffer (2% BSA, 0.1% Tween-20 in 1X PBS) overnight at 4 °C, followed by five washes with washing buffer. Serum samples from immunized mice were serially diluted in blocking buffer. One hundred microliters of each dilution were added to wells and plates were incubated away from light at 37 °C for 1 h. After washing, the appropriate secondary detection antibody was added and incubated at 37 °C for 1 h. Following additional washes, 100 µL/well of TMB substrate (Thermo Fisher Scientific, 34028) was added and incubated away from light at room temperature. The reaction was stopped by adding 100 µL/well of stopping solution (0.16 N H2SO4) and absorbance was read at 450 nm using an ELISA plate reader. Background absorbance from negative control wells (containing blocking buffer without serum) was subtracted from all sample measurements prior to data analysis and visualization67. Outliers were identified using Grubbs’ test (p<0.05) and excluded from subsequent analysis.

SARS-CoV-2 Spike ELISA
For Delta strain analysis, SARS-CoV-2 Super Stable Trimer Spike protein (ACROBiosystems, SPN-C52H9-50UG) was used as the coating antigen. For Omicron strain analysis, SARS-CoV-2 RBD of spike protein (Proteogenix, Strain B.1.1.529, PX-COV-P074) was used. Serum samples were collected from mice immunized with either the B.1.617.2 (Delta) or B.1.1.529 (Omicron) spike protein variant. Standard curves were generated using GraphPad Prism (Version 10.0.1). For Delta, a B.1.617.2 SARS-CoV-2 spike antibody standard (ACROBiosystems, S1N-S58A1) was used. For Omicron, a positive control serum was generated in-house by vaccinating mice with Omicron spike protein in alum adjuvant, and quantified antibody from this serum was used to construct the standard curve. Unknown antibody values were interpolated from the respective standard curves and expressed in ng/mL. The secondary antibody used was Goat anti-mouse IgG, HRP-conjugated (Southern Biotech, 1030-05).

SARS-CoV-2 Nucleocapsid ELISA
Nucleocapsid capture antibody (Acrobiosystem, NUN-CH14) was coated at 4.7 µg/mL. Serum samples from SARS-CoV-2 virally challenged mice were diluted 3-fold from 1:240 to 1:2160. A biotinylated anti-nucleocapsid secondary capture antibody (Acrobiosystem, AM223; 1 µg/mL dilution) was applied for 1 h at 37 °C, followed by streptavidin-HRP secondary (Jackson ImmunoResearch, 016-030-084; 1:1000 dilution) for 1 h at 37 °C. TMB substrate incubation time was 10 min at room temperature. A standard curve was generated from serial 2-fold dilutions of nucleocapsid protein (Acrobiosystems, NUN-C52Hw) ranging from 3.2 ng/mL to 0.05 ng/mL using GraphPad Prism (Version 10.0.2). Unknown sample concentrations were interpolated from the standard curve and expressed in ng/mL.

eGFP ELISA
eGFP protein (Thermofisher Scientific, A42613) was coated at 100 ng/mL. Serum samples from mice immunized with eGFP protein were diluted 3-fold from 1:80 to 1:2160. The Goat anti-mouse HRP-conjugated secondary antibody (Thermo Fisher Scientific, 31430; 1:4000 dilution) was applied for 1 h at 37 °C. TMB substrate incubation time was 20 min at room temperature. An anti-GFP antibody standard (Thermo Fisher Scientific, GFP-101AP) was used to generate the standard curve using GraphPad Prism (Version 9.4.1). Unknown antibody values were interpolated from the standard curve and expressed in ng/mL.

ELISPOT assay protocols
Pre-coated ELISPOT plates were washed with PBS and seeded with spleen cell suspensions (3–5×10⁵ cells/well) in complete medium (RPMI with 10% FBS), with an initial incubation period of 30 min at room temperature for plate blocking. Following overnight rest, lipopolysaccharide (2 µg/mL) and dendritic cells (DC 2.4; 1:10 ratio, 3–5×10⁴ cells/well) were added as antigen-presenting cells. SARS-CoV-2 overlapping spike peptides (JPT Peptide Technologies GmbH, PepMix™; 1 µg/mL) were added for antigen-specific T cell stimulation, optimizing epitope coverage along the protein sequence. Plates were incubated in a humidified chamber at 37 °C with 5% CO₂ for the assay-specific duration. After incubation, plates were washed with PBS, incubated with biotinylated secondary antibody, followed by Streptavidin-HRP, and developed with substrate. Spots were read using an ELISPOT reader system (Autoimmun Diagnostika GmbH, ELR02) and analyzed using GraphPad Prism. Background values were subtracted from all sample measurements prior to data analysis and visualization67. Outliers were identified using Grubbs’ test (p<0.05) and excluded from subsequent analysis.

Interferon-γ ELISPOT. Pre-coated ELISPOT plates (Mabtech, 3321-4HST-2) were blocked with 200 µL of complete medium (RPMI with 20% or 10% FBS). Following overnight cell rest and addition of LPS and dendritic cells, peptides from the SARS-CoV-2 Omicron variant (B.1.1.529) spike protein were added. Plates were incubated for 48 h. Biotinylated secondary antibody (Mabtech, 3321-6) and Streptavidin-HRP (Mabtech, 3310-9) were applied, followed by TMB substrate for spot development.

TNF-α ELISPOT. Pre-coated ELISPOT plates (Immunospot, mTNFap-2M/2) were used without blocking buffer. Following overnight cell rest and addition of LPS and dendritic cells, SARS-CoV-2 spike peptides were added. Plates were incubated for 24 h. Biotinylated secondary antibody and Streptavidin-HRP (both Immunospot, mTNFap-2M/2) were applied, followed by Immunospot Blue Developer solution for spot development.

IL-4 ELISPOT. Pre-coated ELISPOT plates (Immunospot, mIL4p-2M/2) were used without blocking buffer. Following overnight cell rest and addition of LPS and dendritic cells, SARS-CoV-2 spike peptides were added. Plates were incubated for 24 h. Biotinylated secondary antibody and Streptavidin-HRP (both Immunospot, mIL4p-2M/2) were applied, followed by Immunospot Blue Developer solution for spot development.

Measuring viraemia in virally challenged mice
K18-hACE2 transgenic mice were purchased from the Jackson Laboratory and maintained in the Division of Comparative Medicine CL3, Viral Core & Biobank at the University of Toronto. These experiments were approved by the Animal Care Committee (University of Toronto). Animals were maintained and euthanized under humane conditions in accordance with the guidelines of the Canadian Council on Animal Care. In separate experiments, 3 male and 3 female 6–12 week-old K18-hACE2 transgenic mice were used to evaluate viral load in mice vaccinated with 5 µg of LNP-encapsulated Delta (B.1.617.2) spike protein, LNP-encapsulated or naked Omicron (B.1.1.529) spike protein encoded by saDNA, or PBS controls. A second vaccine dose of 5 µg was given 28 days following the initial dose (of 5 µg; both injected intramuscularly) after which virus challenge was presented 14 days later (on Day 42). The LNP-encapsulated Delta (B.1.617.2) spike protein group was challenged with the Delta (B.1.617.2) strain of coronavirus variants administered nasally. While the LNP-encapsulated Omicron (B.1.1.529) spike protein encoded by saDNA or naked saDNA was challenged with the Omicron (B.1.1.529) strain of the SARS CoV-2 coronavirus variant administered nasally. All mice in the Delta (B.1.617.2) strain of coronavirus group were challenged with 1.6×105 viral units/dose of the Delta (B.1.617.2) SARS-CoV-2 virus. The second group consisted of mice vaccinated with saDNA containing the Omicron (B.1.1.529) Spike protein and from mice given no vaccine (i.e., saline only). The mice in this group were vaccinated with the 5 µg of vaccine and on the same schedule as were the mice in the first group. All mice in this group were challenged with 1.0×105 viral units/dose of the Omicron (B.1.1.529) SARS-CoV-2 virus. Serum was collected by cardiac puncture and stored at -20 °C prior to testing.

SARS-CoV-2 pseudotyped virus neutralization assay with GFP reporter
Preparation of SARS-CoV-2 Omicron pseudotyped virus. To generate working batches of SARS-CoV-2 Omicron pseudo-typed virus, HEK293T cells (70%-80% confluent) were transfected with the plasmid pcDNA3.3_SARS2_omicron_BA.1 (Addgene, 180375) using the Lipofectamine 3000 transfection reagent. Approximately 24 h after transfection, cells were infected with the G*ΔG-VSV virus, where the G gene is replaced with the GFP reporter at a multiplicity (MOI) of ~3 to 5. To regenerate working stocks of G*ΔG-VSV virus, cells were transfected with pCAGGS-G and infected with G*ΔG-VSV at low MOI of 0.1 instead. One-hour post-infection, the cell supernatant was removed and the cells were washed with 1X PBS at least three times before replenishing the media with complete culture medium. The first batch of supernatant was collected 24 h after infection and can be stored at 2–8 °C. The cells were then replenished with complete media for another 24 h, after which the supernatant can be collected again. The collected pseudo-typed virus harvests were combined, spun, and filtered through a 0.45 µm filter. One microgram of anti-VSV-G antibody was added to the SARS-CoV-2 Omicron pseudo-typed virus stock and aliquoted into 1 mL cryovials for storage at -80 °C.

Antibody neutralization assay with SARS-CoV-2 Omicron pseudo typed virus. In a clear, 96-well flat-bottom culture plate (Falcon, 08-772-2C), the outermost wells were filled with 200 µL of sterile PBS or water to avoid edged drying effects. Serum sample dilutions were prepared by initially diluting 1:20, followed by two serial 5-fold dilutions. The positive control, anti-SARS-CoV-2 RBD neutralizing antibody (S2K146; ProteoGenix, PTXCOV-A582), was used to create a standard log curve for quantifying antibody titers. The positive antibody had an initial dilution of 1:1000 with serial 3-fold dilutions performed in duplicates. 50 µL of the SARS-CoV-2 Omicron pseudotyped virus stock was mixed with 10 µL of the diluted samples in duplicates. Cell control wells had no serum or virus, while the virus control wells had no serum. The plate was placed in a 37 °C incubator for at least 1 h. After incubation, VERO cells were prepared and adjusted to a cell concentration of 2-3×105 cells/mL with complete DMEM medium. 100 µL of the cell suspension was added to all 60 inner wells, and the plate was incubated in the 37 °C cell culture incubator for 20–28 h. After incubation, the plates were spun at 600xg for 5 min to bring the cells to the bottom of the wells. The cells were then fixed with 4% PFA pH 7.4 and stained with 300 nM DAPI. The plates could be stored at 2–8 °C however it is recommended to measure the plate as soon as possible since the fluorescence will diminish over time even when fixed. To assess and quantify cells exhibiting fluorescence, the CellInsight CX5 High Content Screening (HSC) instrument (Thermo Fisher Scientific) was used to read the neutralization assay plates. Software assay parameters were set to measure GFP and DAPI fluorescence in the cells. Positive GFP cells were only considered if they overlapped with DAPI-positive cells to differentiate them from cellular debris. The raw dataset was exported as an Excel spreadsheet.

To calculate the concentration of neutralizing antibodies in the serum or tested samples, the exported raw data was first used to calculate percent neutralization and then interpolated against the standard curve generated. Percentage neutralization was calculated as follows: (1.0-[percent of GFP from samples/percent of GFP from virus control samples]) x 100. A standard log scale was generated by plotting the log of antibody concentrations against the readout measurements. The concentration of neutralizing antibodies in the samples was then interpolated from the log standard curve which was generated from the known concentrations of antibody S2K146.

Estimation of frequency of genomic integration
Within the Supplementary information, the Supplementary Method for determining the frequency of genomic integration, along with corresponding references is included. The methods and results are further explained in Supplementary Fig. S6 and 7, and Supplementary Tables S1 and S2.

Statistical analysis
Vaccine data was first analysed for significant outliers in GraphPad Prism (Version 9.4.1 or 10.0.0) using Grubbe’s test. This data was then analysed using the Psych package in RStudio (R version 4.2.0). The resulting summary statistics were used to assess skewness and kurtosis of data distribution. Shapiro-Wilk and Kolmogorov-Smirnoff tests were performed in R to measure the parameters of normal distributions. Normally distributed data was subjected to Student’s t-test (for two groups) where error bars represented standard deviation (SD), or Analysis of Variance (ANOVA) statistical test (both using the GraphPad Prism software, version 9.4.1 or 10.0.0) along with Tukey’s and Dunnett’s post-hoc tests to test the differences between more than two groups. Each point on the Figure denotes individual animal in the experiment. p-values <0.05 were considered significant using 95% confidence intervals.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Jefferies et al. claimed the development of a binary self-amplifying nucleic acid platform that could eliminate the requirement of vectors in vaccine applications. However, many design of their experiments were poor and evidences/data did not support their claims. It looks like they are over-selling their platform. It is not recommend for publication in this high-quality journal.\nMajor issues:\n1. SaRNAs have long been developed and proposed as a vaccine platform. Their corresponding plasmid (i.e., saDNA) were also designed and used for IVT production of saRNA. We did not see a unique design of self-amplifying nucleic acid platform was developed such as using an improved replicon to facilitate the elimination of lipid nanoparticles and the mechanism was disclosed (why this design could enable the elimination of vectors). It seems that there is no improvement in design compared to reported ones (10.1016/j.ymthe.2017.11.017; 10.1038/s41467-020-17409-9; 10.1016/j.ymthe.2021.04.001.).\n2. Experiments were poorly designed. The authors should compare LNP-saDNA, LNP-saRNA, saDNA, saRNA and LNP-mRNA throughout their studies if they intended to demonstrated the superiority of their self-amplifying nucleic acid platform. However, many studies were lack of experimental groups. Moreover, the authors used different LNPs (DOTAP) when comparing their vaccines with LNP-mRNA (SM-102). Further, the author used different doses for different vaccines, which made their comparison unfair. In some animal studies, the authors vaccinated mice once, while in others, the authors vaccinated mice twice, which made it more difficult to compare the efficacy.\n3. The in vitro/vivo expression kinetics of LNP-saDNA, LNP-saRNA, saDNA, saRNA and LNP-mRNA should be thoroughly studied over a longer period. The time point of expression peak should be reflected. For in vivo expression, luciferase is recommended as a reporter gene to enable consecutive, long-term observation (> 1 month).\n4. DNA and AAV should be used and compared to Gemini-D in order to support their claim about lower genetic integration.\n5. A major concern of saDNA and saRNA is toxicity. The reactogenicity/inflammation (e.g., serum TNF-alpha, IP-10 and MCP-1) should be studied in vivo and compared with mRNA-LNP.\n6. It is not fair to compare the integrity of saDNA, saRNA with mRNA-LNP after repeated freezing and thawing. SaDNA and saRNA are molecules, while mRNA-LNP is a complex. Also, mRNA-LNP is not designed for repeated freezing and thawing. Instead, the thermostability/integrity of cargoes should be compared between saDNA, saRNA and mRNA-LNP.\n7. IgG data from mice should not be compared to human IgG data. Could the authors give examples where IgM is important for vaccine development?\n8. GFP was used as antigen. Please justify it. It is recommended that Spike is used as antigen to keep consistent.\nMinor issues\n9. The Introduction (especially at the beginning) is too broad and deviated from scope of the work.\n10. Page 47, line 5, it should be LNP-encapsulated mRNA.\n11. Figure 4D and 8A, there are too limited replicates/mice in each group (n = 2). In many graphs (Figures 5, 8), each data point should be shown.\n12. Figure 4c, a scheme is needed to show the workflow of this experiment.\n13. Figure 5, The GFP signals in DNA and RNA seem stronger than saDNA and saRNA.\n14. Page 10, line 10. Figure 5D is wrong.\n15. Some sentences are repetitive. Page 12, line 1, this sentence can be combine with the last one. And Page 18, line 9.\n16. In all figures, please use LNP-saDNA and naked saDNA to differentiate them. The same to saRNA.", "reviewer_2": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_3": "The manuscript by Jefferies et al details the creation of lipid nanoparticle free self-amplifying nucleic acid vaccine platforms, with reported benefits over conventional nanomedicines that if true could provide significant advancements for this type of therapy/vaccine platforms. The authors claim to benchmark their platforms against conventional mRNA, but there are limited head-to-head comparison or studies not designed appropriately to enable direct comparison. While the authors demonstrate freeze-thaw stability and T cell and antibody responses are induced post-vaccination, claims of superiority to current mRNA LNP technologies are not supported by current data and therefore precludes publication of the manuscript at this point in time.\nMajor comments:\nComparison studies not performed at the same time: Data in figure 3 and figure 4 appears to be derived from independent experiments (based on differences in background population in flow plots and gates). It feels as though the LNP mRNA was included as a request from a previous reviewer, and is there to highlight difference in length of antigen expression, which is important data to show. But if the authors are including this data, then they must clearly state data was acquired in independent experiments and not analyse data together in a single statistical test.\nStatistical analysis primarily compare response to naïve control: if the focus of the immunology study is to show the vaccine is immunogenic, then this analysis would be appropriate, but the underlying tone of the paper is comparison of platforms, therefore the statistical analysis should be focussed on comparing vaccine groups and p values on plots indicating these differences (or lack of which there predominately is).\nImmunogenicity experiments performed with different doses of vaccine: Figure 8 is included to demonstrate that LNP formulation isn’t required, but there is a large range in antigen dose 100ug Gemini-D, 25ug Gemini-R and 5ug LNP mRNA. Overall the data shows no difference in immunogenicity, but if the dose of antigen was normalised then LNP vaccines would show vastly superior responses. If it isn’t possible to have equivalent antigen doses between platforms, then a head to head comparison in a dose ranging study for each vaccine should be performed, this would give the reader confidence that the vaccine doses weren’t cherry picked.\nLack of direct head to head comparison: Fig 9 investigates the duration of antibody responses, and suggest naked saDNRA or saRNA “result in extended and stronger antibody responses” but compared to what, there is no comparator vaccine in this study. The claim of superiority needs to be tempered.\nFig 10 compares the efficacy of naked vs saRNA, each group is compared to naïve controls then reduction in viral load between groups compared. This analysis should all be performed in a single statistical analysis and presented in a single graph if the experiment was performed at the same time with the same naïve controls, otherwise this is not a proper head to head comparison.\nMinor comments:\nThere is a lack of attention to detail across the paper and doesn’t give the reader confidence in the data.\nFigure 5 contains images of the same magnification, but then there is differences between size bars, indicating images have been stretched or not at the same scale.\nFigure 8B not all data points are displayed and the error bar is cropped from the top of the graph.\nFigure 8A IgM contains only 2 data points but was an experiment of 4 (?) mice.\nUnvaccinated control data is not shown, yet this is the focus of the statistical analysis.\nDose and constructs shift between experiments. Figure legends lack detail on number of replicate experiments, dose of vaccine and particular vaccine construct.", "reviewer_4": "In this manuscript, the authors compare a self-amplifying nucleic acid platform (mRNA and armed DNA) with LNP-formulated nucleic acid vaccines to show that LNP formulation may be omitted to obtain good vaccine responses.\nThe system is based on the “Gemini” replicon-based self-amplifying dual expression vector which contains both a T7 promoter for in vitro transcription and a CMV promoter for mRNA production if delivered as DNA in cells or tissues. The authors confirm the presence of negative strand RNA synthesis after transfection of the Gemini system using a GFP expression-based Gemini approach first, followed by proof of SARS-CoV-2 Delta Spike protein production.\nThe vaccine platforms described are very interesting and promising, however they require more in vivo work for proper validation as I suggest below:\nIs the decline in GFP expression observed in vitro after LNP-mRNA transfection due to dying cells or is this exhaustion of the mRNA pool used for transfection?\nLine 4 page 11: what is blue ice? Dry ice?\nIn Fig 3, the Gemini system is delivered using LNP formulation to facilitate transfection. In other figures or in vivo, no LNP formulation is mentioned and I assume not used for delivery of the Gemini system. It would add to the clarity of the manuscripts if this was made more clear when LNP formulation was actually used or not.\nFig. 6: can the gel bands be quantified to provide a more quantitative measure of degradation/stability for the different vaccine types? Typo in the legend: … gel images were documents… should be …. gel images were documented…\nPage 14: typo: signally needs to be signaling.\nFigure 8: please show the values for the unvaccinated control groups in all panels as well. Panel B: error bar is not fully displayed, Panel C: how many mice per group?\nPage 13-14: the authors suggest that different TLR signaling may be the reason for the different outcomes of the antibody response. Unmethylated DNA and RNA can also be sensed by innate immune sensors other than TLRs. It is likely that the cGAS-STING pathway will be involved in sensing as well.\nI would suggest that a microneutralisation assay needs to be done with the immune sera of vaccinated mice to correlate ELISA binding titers with more functional antibodies that can neutralize virus. This will help to understand better the quality of the vaccine response.\nPage 17: the values for antibody responses to saRNA should also be shown until day 84 post vaccination to allow fair comparison between the saRNA and saRNA and saDNA system. Was an LNP-formulated mRNA control included in this durability study. Again, microneutralization titers generated with these sera would be more informative than ELISA binding titers alone.\nPage. 17 line 12: typo in paragraph title\nThe protection experiment shown in Fig. 10 raises many questions: Omicron variants show very poor replication and cause no disease in animal models. Which Omicron variant was used for challenge. Why was nucleocapsid protein in blood used as a read out for viral load? Plaque assay, TCID50 or even qPCR for subgenomic RNA would make more sense. What was the rationale for challenging mice at 5 days post booster vaccination. This is very short after vaccination, and antibody titers will still go up for many days post booster vaccination. Presence of nucleocapsid protein in blood does not perse mean blood viremia, as stated by the authors. It would have made more sense if the authors had used the Delta-based vaccines and had challenged with the Delta variant, which actually is pathogenic in K18 mice."}, "author_response": "General Response:\nWe sincerely appreciate the reviewer’s thoughtful comments and the opportunity to address their concerns. While we respectfully differ with the assertion that our Gemini platform is being \"over-sold\" and that our data do not substantiate our claims, we believe the evidence we present offers compelling and reproducible support for the platform's novel design, robustness, and transformative potential in vaccine technology.\nWe are particularly encouraged by the positive feedback from the other two reviewers, who recognized the novelty and significance of our work and expressed no concerns about its suitability for Nature Communications.\nTo address the reviewer’s concerns and ensure our manuscript aligns with the highest standards of clarity and balance, we have carefully revised the text to tone down any elements that could be perceived as over-selling the technology. At the same time, we have worked to maintain a clear emphasis on the platform's novelty and its suitability for publication in Nature Communications.\nIn the response below, we thoroughly address the reviewer’s specific comments, providing further clarification and highlighting the comprehensive advantages of our approach. We hope this demonstrates why the Gemini platform represents a meaningful contribution to the field and merits serious consideration for publication in this prestigious journal.\nHighlights of the Dual-Format Innovation:\nThe Gemini platform is a binary system that combines the best features of self-amplifying RNA (saRNA) and self-amplifying DNA (saDNA) technologies. This dual-format approach is indeed novel and offers two distinct advantages:\nGemini-R (RNA-based): Delivers rapid antigen expression, ideal for emergency responses or acute vaccination scenarios.\nGemini-D (DNA-based): Provides exceptional stability, simplified manufacturing, and long-term storage solutions.\nThese complementary technologies allow for greater flexibility and adaptability, something that no other single-platform system currently offers. While saRNA platforms based on Venezuelan equine encephalitis virus (VEEV) are well studied, the application of a self-amplifying armed DNA (saDNA) framework, especially as part of a binary vaccine system, remains completely unexplored. This addresses a critical gap in the literature, emphasizing the platform’s novelty.\nManufacturing Efficiency:\nThe Gemini platform’s ability to eliminate the need for lipid nanoparticle (LNP) encapsulation is a direct response to some of the most challenging bottlenecks faced by current mRNA vaccines. Conventional mRNA-based vaccines are reliant on LNPs for stability and delivery, which adds complexity and cost to production. In contrast:\nGemini-D leverages a plasmid DNA-based vector that is self-amplifying, allowing for simpler, scalable manufacturing. This represents a tangible improvement in production economics and logistics, especially in resource-limited settings where LNP formulations are difficult to implement.\nOur data clearly show significant reductions in adverse reactions due to the absence of LNPs, a well-known challenge in current mRNA vaccine systems.\nCost-Effectiveness and Scalability:\nCritically, Gemini-D’s plasmid-based system enables low-cost, high-volume manufacturing with minimal reliance on sophisticated equipment, which can be a significant advantage for rapid global deployment. The absence of LNPs directly reduces production costs and complexity, making the platform a viable option for large-scale manufacturing under standard conditions.\nEnhanced Stability and Distribution:\nOne of the strongest points of the Gemini platform is its enhanced stability, which the reviewer overlooks:\nGemini formulations are stable across multiple freeze/thaw cycles and can be freeze-dried, stored, and reconstituted without losing efficacy. This contrasts with current mRNA vaccines that degrade rapidly after just one freeze/thaw cycle and require ultra-cold storage (-20°C to -80°C).\nThe ability to store and transport Gemini formulations at ambient temperatures (2°C to 8°C) offers substantial benefits in terms of global distribution, particularly in remote or low-resource areas where maintaining cold chain logistics is a major hurdle.\nProlonged Protein Expression and Immunogenicity:\nOur studies demonstrate that the Gemini platform supports prolonged protein expression for over 28 days, compared to the mere 3-day window observed with traditional mRNA vaccines. This extended expression period leads to a sustained immune response—a critical aspect of durable and effective immunization strategies. We further substantiate this with preclinical models showing that the self-amplifying DNA format elicits robust antibody responses and mitigates viraemia, which is key for reducing pathogen replication and transmission.\nPayload Capacity:\nThe Gemini platform can accommodate payloads up to 20 kb, far surpassing the 4.18 kb limit of most current mRNA vaccines. This allows for more complex or multivalent vaccines, opening the door to combination therapies that require the expression of multiple antigens or larger therapeutic proteins.\nAddressing Specific Claims of Over-Selling:\nWe sincerely thank the reviewer for their feedback and appreciate the opportunity to address these points in greater detail. It is not our intent to \"over-sell\" the Gemini platform, but rather to emphasize its genuine advantages, which are firmly supported by rigorous, data-driven results:\nSafety and logistics improvements: Our claims regarding the platform’s ability to remove the need for lipid nanoparticles (LNPs) are strongly supported by experimental data, which demonstrate enhanced safety, reduced toxicity, and simplified logistics compared to existing systems.\nExperimental rigor: The suggestion that our experimental designs were \"poor\" does not reflect the care and rigor with which our studies were conducted. All experiments were designed with appropriate controls and statistical validation to ensure reliability and reproducibility. Furthermore, we have meticulously conducted additional experiments and provided new data to strengthen the manuscript and address any potential concerns about the robustness of our findings.\nConclusion:\nThe Gemini platform represents a meaningful advancement in vaccine and therapeutic delivery by addressing critical limitations of existing nucleic acid-based platforms, including scalability, stability, cost, and immunogenicity. Its binary system, leveraging both saRNA and saDNA, offers unparalleled flexibility and efficacy, setting it apart from current technologies.\n[Redacted]\nTo address the reviewer’s concerns, we have carefully revised the manuscript to tone down language that might be perceived as over-selling, while continuing to highlight the platform's genuine advantages and suitability for Nature Communications. In addition to rewriting key sections, we have incorporated new experiments and data that further substantiate the robustness and novelty of the Gemini platform. Furthermore, we have included a new graphical abstract to provide a concise and visual summary of the platform's key features and benefits.\n[Redacted]. The Gemini platform’s unique features, including its dual-format system, cost-effectiveness, and improved stability, underscore its relevance and significance for publication in this high-impact journal. We are grateful for the reviewer’s thoughtful input and the opportunity to share this work.\nSpecific Responses to Reviewer #1:\nWe sincerely thank the reviewer for their detailed feedback, which has helped us further refine and improve our manuscript. In response to the comments, we have undertaken significant revisions, including a complete rewrite of the manuscript to address concerns about tone and the strength of our claims. Additionally, we have added new experiments and repeated several of the original experiments to ensure the data is as robust and comprehensive as possible.\nWe would like to respectfully address the comment regarding the suitability of the Gemini platform for publication. While we understand the importance of critical evaluation, we believe this particular assertion does not reflect the current standing and recognition of the platform. The Gemini platform provides enhanced effectiveness, cost-efficiency, and accessibility, offering significant advantages over conventional vaccine technologies and presenting promising solutions for both current and future therapeutic needs.\n[Redacted]\nWe deeply appreciate the reviewer’s comments, which have prompted us to present the strengths of the Gemini platform with greater clarity and balance. We hope that the extensive revisions, new data, and additional context provided will address the reviewer’s concerns and demonstrate why this work is well-suited for publication in this esteemed journal.\nThe following experiments were added.\n1. Antibody Responses Induced by Vaccine Formats: To evaluate the antibody responses induced by the Gemini-R and Gemini-D vaccine formats expressing the SARS-CoV-2 B.1.617.2 (Delta) spike variant, we tested K18-hACE2 transgenic mice. We injected 5 µg of either LNP-encapsulated Gemini-R or Gemini-D vaccines and observed that both formats elicited statistically significant antibody responses compared to unvaccinated controls (ANOVA, p = 0.0082, Figure 10D). Specifically, the IgG response to the Gemini-D format was significantly higher (p = 0.0046) than the unvaccinated control, though the Gemini-R format also showed a notable IgG response, albeit lower than Gemini-D (p = 0.1019, Figure 11B). Conversely, the IgM response was higher in the Gemini-R group (p = 0.0420) compared to the Gemini-D group (p = 0.1525, Figure 11C). Neither vaccine format induced a significant IgA response, nor did we observe any significant toxicity, such as weight loss (p > 0.05, data not shown). Our antibody quantitation aligns with clinical data, showing that both Gemini formats elicit robust responses with IgG concentrations significantly higher than those typically observed in SARS-CoV-2 patient sera (~200 ng/ml).\nFigure 10\nFigure 11\n2. IgM plays a pivotal role in vaccine development, mainly due to its unique properties and early response in the immune system. As the first antibody produced during an immune response, IgM is essential for the initial defence against infections. In the context of vaccine development, this early response is critical for evaluating the efficacy of a vaccine candidate. Vaccines aim to mimic natural infection to elicit an immune response without causing disease, and the presence of IgM serves as an early indicator of the vaccine's ability to trigger an immune response. Moreover, IgM's pentameric structure allows it to effectively agglutinate pathogens, leading to enhanced pathogen clearance. This property is particularly important in vaccines targeting bacteria and viruses that rely on agglutination for effective neutralization. For instance, in the development of vaccines against encapsulated bacteria, such as Streptococcus pneumoniae, the IgM response can be a crucial measure of vaccine-induced immunity. Additionally, IgM has a high avidity for antigens, which is beneficial in the context of vaccines designed to elicit responses against highly variable pathogens, like influenza or HIV. In such cases, the ability of IgM to recognize a broad range of antigenic variants can provide an early line of defence against these rapidly mutating pathogens. Furthermore, the role of IgM in the maturation of the immune response is significant. The early IgM response can shape the subsequent IgG response, which is more specific and provides long-term immunity. Understanding how vaccines stimulate this transition from an IgM to an IgG response is essential in developing vaccines that provide lasting protection. In conclusion, IgM's role in the early immune response, its agglutinating ability, high avidity for antigens, and its influence on the maturation of the immune response make it a critical component in vaccine development. Its presence and functionality can significantly influence the design, testing, and evaluation of vaccines, particularly those targeting rapidly mutating or highly variable pathogens.\nReferences:\nRossi CM, Lenti MV, Merli S, Di Sabatino A. Role of IgM Memory B Cells and Spleen Function in COVID-19. Front Immunol. 2022 Jun 30;13:889876. doi: 10.3389/fimmu.2022.889876. PMID: 35844543; PMCID: PMC9280616.\nLiu J, Wang Y, Xiong E, Hong R, Lu Q, Ohno H, Wang JY. Role of the IgM Fc Receptor in Immunity and Tolerance. Front Immunol. 2019 Mar 22;10:529. doi: 10.3389/fimmu.2019.00529. PMID: 30967868; PMCID: PMC6438924.\nPaces J, Strizova Z, Smrz D, Cerny J. COVID-19 and the immune system. Physiol Res. 2020 Jul 16;69(3):379-388. doi: 10.33549/physiolres.934492. Epub 2020 May 29. PMID: 32469225; PMCID: PMC8648321.\nGasser R, Cloutier M, Prévost J, Fink C, Ducas É, Ding S, Dussault N, Landry P, Tremblay T, Laforce-Lavoie A, Lewin A, Beaudoin-Bussières G, Laumaea A, Medjahed H, Larochelle C, Richard J, Dekaban GA, Dikeakos JD, Bazin R, Finzi A. Major role of IgM in the neutralizing activity of convalescent plasma against SARS-CoV-2. Cell Rep. 2021 Mar 2;34(9):108790. doi: 10.1016/j.celrep.2021.108790. Epub 2021 Feb 10. PMID: 33596407; PMCID: PMC7874916.)\n3. Immunogenicity Without LNP Encapsulation: We assessed whether LNP encapsulation was necessary for the immunogenicity of Gemini saRNA and saDNA vaccines by using eGFP as a model antigen. Our results demonstrated that Naked saDNA (50 µg) performed better (p = 0.0129) than 5 µg of LNP-encapsulated saDNA (p = 0.1983), while Naked saRNA (50 µg) also performed better (p = 0.0420) compared to its LNP-encapsulated counterpart (p = 0.3200) (Figure 10B-C). This suggests that LNP encapsulation may not be essential for eliciting a strong immune response. We further compared antibody responses among different vaccine formulations and found that Naked saDNA and Naked saRNA had comparable or better responses compared to LNP-encapsulated vaccines (Figure 10D-E). T cell responses measured by IFN-γ, IL-4, and TNF-α ELISPOT assays showed that Naked formats achieved similar or superior responses compared to LNP-encapsulated vaccines (Figures 10F-K). These findings indicate that Naked Gemini vaccines are highly effective and could potentially reduce formulation costs and complexity.\n4. Durability of Antibody Responses: We conducted a time-course study to evaluate the durability of antibody responses elicited by Naked saDNA and saRNA vaccines expressing Omicron-Spike (Figure 12A). Our results showed that Naked saRNA vaccines provided durable responses up to 42 days, whereas Naked saDNA vaccines elicited durable responses lasting at least 70 days (Figure 12B). This extended durability of Naked saDNA responses suggests that it may be preferable for applications requiring long-term immune protection.\nViral Challenge and Vaccine Efficacy: To determine the efficacy of Naked saDNA compared to LNP-encapsulated saDNA, we performed viral challenge experiments. Mice were vaccinated with either Naked or LNP-encapsulated Omicron-Spike saDNA and challenged with SARS-CoV-2. We observed a significant reduction in viraemia in vaccinated mice compared to controls (Figure 13A-C). Notably, Naked saDNA vaccines demonstrated a marked reduction in nucleocapsid protein levels (p = 0.0003) and similar neutralization antibody levels to Naked saRNA vaccines (Figure 13C). This reduction in viraemia is crucial for developing effective vaccines that could potentially reduce severe respiratory outcomes associated with COVID-19.\nSummary:\nWe sincerely thank the reviewer for their thoughtful and detailed feedback, which has significantly helped us improve the clarity and presentation of our manuscript. In response, we have undertaken substantial revisions, including a complete rewrite of the text to address concerns about tone and claims, as well as the addition of new experiments and repetitions of key experiments to further strengthen our conclusions.\nTo more accurately summarize the technology and results, we have now included graphic summaries for each experiment in the manuscript, along with a concise and visually engaging graphical abstract. We believe these additions enhance the accessibility and impact of the paper, making it easier for readers to appreciate the novelty and significance of the Gemini platform.\nWe greatly value the reviewer’s expertise and insights, which have inspired us to refine and present our work with even greater precision. We are confident that the revised manuscript demonstrates the robustness, innovation, and broad applicability of the Gemini platform, and we hope it now aligns with your expectations the high standards of this prestigious journal.\nGraphical Abstract\nGraphical Abstract Legend:\nConventional mRNA Vaccine Impact: Conventional mRNA-based vaccines were critical in reducing the burden on healthcare systems and lowering mortality rates during the COVID-19 pandemic. However, despite their success, they faced significant technological challenges.\nTechnological Challenges in mRNA Vaccines: The main issues with mRNA vaccines included stability concerns, complex manufacturing processes, and the need for lipid nanoparticle (LNP) encapsulation. These challenges complicated vaccine production, distribution, and long-term storage, especially in resource-limited settings. Gemini Platform Overview: The Gemini platform represents a breakthrough in gene expression technology, utilizing both self-amplifying RNA (saRNA) and self-amplifying armed DNA (saDNA). This binary platform addresses many of the limitations faced by conventional mRNA vaccines. Stability and Storage: Unlike conventional mRNA vaccines, which degrade after one freeze-thaw cycle, the Gemini platform demonstrates exceptional stability through five freeze-thaw cycles. It can also be freeze-dried, stored, and distributed as a powder that can be reconstituted in aqueous solutions, providing significant long-term storage benefits. LNP Elimination and Manufacturing Simplification: A key strength of the Gemini platform is that both the saRNA and saDNA technologies bypass the need for LNP encapsulation, which is essential for mRNA vaccines like those from Moderna and Pfizer. This elimination of LNPs simplifies the manufacturing process, reduces associated costs, and mitigates potential toxicity and adverse reactions seen with LNPs. Cold Chain Management: Unlike mRNA vaccines, which require stringent refrigeration conditions (e.g., -20°C to -80°C), the Gemini platform formulations can be stored at ambient temperatures between 2°C and 8°C. This significantly improves cold chain management and reduces logistical challenges, particularly in remote or resource-limited settings. Extended Protein Expression: The Gemini platform offers prolonged protein expression for over 28 days, compared to the three days seen in conventional mRNA vaccines. This extended expression supports more robust and sustained immune responses, including both humoral antibodies and cell-mediated T lymphocytes. Payload Capacity: Another critical advantage of the Gemini platform is its ability to carry payloads of up to 16-20 kb, far exceeding the 4.18 kb limit of mRNA vaccines like those from Moderna and Pfizer. This larger payload allows for the expression of more complex or larger proteins, offering potential for multivalent vaccines and combined immunotherapies. Safety and Integration: The Gemini saRNA and saDNA platforms are several orders of magnitude safer than FDA standards for vector integration, reducing the risk of insertional mutagenesis. Viraemia Reduction: The naked self-amplifying armed DNA format of the Gemini platform has been shown to provide durable antibody responses and holds promise for curtailing viraemia, potentially reducing SARS-CoV-2 replication and transmission. Cost-Efficiency and Accessibility: Overall, the Gemini platform offers enhanced cost-efficiency and accessibility, making it a superior alternative not only for vaccines but also for the delivery of immunotherapeutics and other biologics. Broader Nanomedicine Applications: Beyond vaccines, the Gemini platform represents a significant advancement in nanomedicine, with applications in vaccine development, cancer treatment, and therapeutic protein delivery, demonstrating its versatility and broad potential."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors improved the manuscript in their revision, but not enough to justify the publication in this journal. First, the rationale of this study is poor. Naked plasmid DNA vaccines and RNA vaccines have long been developed and successfully triggered adaptive immune responses (DOI: 10.1126/science.282.5388.476; DOI: 10.1038/s41541-021-00419-z; DOI: 10.1007/s00262-016-1869-7). India even marketed a naked plasmid DNA-based COVID-19 vaccine ZyCoV-D delivered by a needle-free device in 2021. However, due to the poor delivery efficiency and low efficiency to enter the cell nucleus, a high dose of nucleic acid vaccine is needed to trigger moderate immune responses (e.g., 2 mg/dose for three doses of ZyCoV-D vs 30 μg/dose for two doses of BNT162b2 mRNA-LNP vaccine; protection efficacy ~67% vs ~95%). The reason for the use of LNP in various nucleic acid vaccines is that it can enhance their stability, increase their intracellular delivery and subsequent antigen expression, and also serve as an adjuvant to boost adaptive immune responses, all of which contribute to vaccine efficacy at a low dose. While the authors developed naked plasmid saDNA (instead of traditional plasmid DNA), it still needed a much high dose (Figure 8) to achieve immune responses comparable to LNP-formulated one (100 μg vs 5 μg). Second, it is well known that plasmid DNA and unmodified RNA can trigger strong inflammation and side effects, which was exactly observed in saDNA and saRNA (TNF, IL-6 in Figure 9). Therefore, despite greater thermostability and simpler manufacturing, naked saDNA/saRNA exhibit limited real-world applicability. Moreover, although the authors included more data in the revision, their experiments (especially groups and doses) were lack of scientific consistency, rigor and integrity. They are even not using the state-of-the-art LNP (e.g., SM-102 LNP and ALC-0315 LNP) to encapsulate their cargo, which further decreases the significance of this work. The major novelty of this work is that the authors developed a naked saDNA vaccine platform in contrast to traditional plasmid DNA while the design of saRNA is the same to previous studies. Therefore, it seems more reasonable to just systematically compared saDNA with DNA in their re-organized story.\nPage 6, the authors concluded that “a fundamental challenge in the development of all LNP-based vaccines and therapeutics is the need to maintain a precise ratio between the nucleic acid payload and the LNP formulation”. This claim is arbitrary and wrong.\nPage 9, should “six weeks” be “four weeks”?\nPage 15, “concentrations” should be “doses”. “The mRNA group showed the lowest cytokine levels” this claim is not correct.\nPage 17 and 18, there is no LNP-encapsulated vaccine group in Figure 11 as the authors claimed.\nPage 20, why is nucleic acid-to-LNP ratio fixed at 2.5:1? Is this weight ratio or molar ratio?\nPage 21, “If an excess of cationic lipid is used, it can result in overly charged nanoparticles that may lead to aggregation, affecting the uniformity and stability of the LNPs.” This claim is arbitrary and wrong.\nFigure 4, why did the authors use LNP-formulated saDNA/saRNA for this in vitro study considering they aimed to omit LNP in their vaccines?\nFigure 5C, the authors deliberately lowered the intensity of florescence in their revision without any justification.\nFigure 7B, why there are two bands after FD?\nFigure 9, the authors used only two mice per group, which is improper.\nFigure 10, the data is poorly presented and misleading.\nAll figures, dot plot is suggested throughout the figures.\nThe authors did not respond to my previous suggestion “IgG data from mice should not be compared to human IgG data.”", "reviewer_2": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_3": "Authors addressed my major concerns with the manuscript"}, "author_response": "Reviewer #1 (Remarks to the Author): ......................................................................................................... 2\nReviewer’s General Comment: ................................................................................................................. 2\nAuthor’s Response: ................................................................................................................................... 2\nReviewer’s Major Issues and Author’s Responses: ................................................................................... 5\n1. SaRNAs have long been developed and proposed as a vaccine plaHorm. Their corresponding plasmid (i.e., saDNA) were also designed and used for IVT producNon of saRNA. We did not see a unique design of self-amplifying nucleic acid plaHorm was developed such as using an improved replicon to facilitate the eliminaNon of lipid nanoparNcles and the mechanism was disclosed (why this design could enable the eliminaNon of vectors). It seems that there is no improvement in design compared to reported ones (10.1016/j.ymthe.2017.11.017; 10.1038/s41467-020-17409-9; 10.1016/j.ymthe.2021.04.001.). ........................................................................................................... 5\n2. Experiments were poorly designed. The authors should compare LNP-saDNA, LNP-saRNA, saDNA, saRNA and LNP-mRNA throughout their studies if they intended to demonstrated the superiority of their self-amplifying nucleic acid plaHorm. However, many studies were lack of experimental groups. Moreover, the authors used different LNPs (DOTAP) when comparing their vaccines with LNP-mRNA (SM-102). Further, the author used different doses for different vaccines, which made their comparison unfair. In some animal studies, the authors vaccinated mice once, while in others, the authors vaccinated mice twice, which made it more difficult to compare the efficacy. ................. 8\n3. The in vitro/vivo expression kineNcs of LNP-saDNA, LNP-saRNA, saDNA, saRNA and LNP-mRNA should be thoroughly studied over a longer period. The Nme point of expression peak should be reflected. For in vivo expression, luciferase is recommended as a reporter gene to enable consecuNve, long-term observaNon (> 1 month). .............................................................................. 10\n4. DNA and AAV should be used and compared to Gemini-D in order to support their claim about lower geneNc integraNon. ................................................................................................................... 13\n5. A major concern of saDNA and saRNA is toxicity. The reactogenicity/inflammaNon (e.g., serum TNF-alpha, IP-10 and MCP-1) should be studied in vivo and compared with mRNA-LNP. .................. 15\n6. It is not fair to compare the integrity of saDNA, saRNA with mRNA-LNP ager repeated freezing and thawing. SaDNA and saRNA are molecules, while mRNA-LNP is a complex. Also, mRNA-LNP is not designed for repeated freezing and thawing. Instead, the thermostability/integrity of cargoes should be compared between saDNA, saRNA and mRNA-LNP. .......................................................... 16\n7. IgG data from mice should not be compared to human IgG data. Could the authors give examples where IgM is important for vaccine development? ............................................................................ 18\n8. GFP was used as anNgen. Please jusNfy it. It is recommended that Spike is used as anNgen to keep consistent. ........................................................................................................................................... 19\nReviewer’s Minor Issues and Author’s Responses: ................................................................................. 21\n9. The IntroducNon (especially at the beginning) is too broad and deviated from scope of the work.\n............................................................................................................................................................ 21\n10. Page 47, line 5, it should be LNP-encapsulated mRNA. ................................................................ 21\n11. Figure 4D and 8A, there are too limited replicates/mice in each group (n = 2). In many graphs (Figures 5, 8), each data point should be shown. ............................................................................... 21\n12. Figure 4c, a scheme is needed to show the workflow of this experiment. ................................... 24\n13. Figure 5, The GFP signals in DNA and RNA seem stronger than saDNA and saRNA. .................... 25\n14. Page 10, line 10. Figure 5D is wrong. ............................................................................................ 27\n15. Some sentences are repeNNve. Page 12, line 1, this sentence can be combined with the last one. And Page 18, line 9. ............................................................................................................................ 28\n16. In all figures, please use LNP-saDNA and naked saDNA to differenNate them. The same to\nsaRNA. ................................................................................................................................................. 29\nConclusion: ............................................................................................................................................. 31\nReviewer #1 (Remarks to the Author):\nReviewer’s General Comment:\nJefferies et al. claimed the development of a binary self-amplifying nucleic acid platform that\ncould eliminate the requirement of vectors in vaccine applications. However, many design of\ntheir experiments were poor and evidences/data did not support their claims. It looks like they\nare over-selling their platform. It is not recommend for publication in this high-quality\njournal.\nAuthor’s Response:\nWe acknowledge the reviewer’s comments and the opportunity to address their concerns. While\nwe respectfully differ with the assertion that our Gemini platform is being \"over-\nsold\" and that our data do not substantiate our claims, we believe the evidence we present offers compelling and reproducible support for the platform's novel design, robustness, and\ntransformative potential in vaccine technology.\nWe are particularly encouraged by the positive feedback from the other two reviewers, who\nrecognized the novelty and significance of our work and expressed no concerns about its suitability\nfor Nature Communications.\nTo address the reviewer’s concerns and ensure our manuscript aligns with the highest standards of\nclarity and balance, we have carefully revised the text to tone down any elements that could be\nperceived as over-selling the technology. At the same time, we have worked to maintain a clear\nemphasis on the platform's novelty and its suitability for publication in Nature Communications.\nIn the response below, we thoroughly address the reviewer’s specific comments, providing further\nclarification and highlighting the comprehensive advantages of our approach. We hope this\ndemonstrates why the Gemini platform represents a meaningful contribution to the field and merits\nserious consideration for publication in this prestigious journal.\nHighlights of the Dual-Format Innovation:\nThe Gemini platform is a binary system that combines the best features of self-amplifying RNA\n(saRNA) and self-amplifying DNA (saDNA) technologies. This dual-format approach is indeed\nnovel and offers two distinct advantages:\n• Gemini-R (RNA-based): Delivers rapid antigen expression, ideal for emergency\nresponses or acute vaccination scenarios.\n• Gemini-D (DNA-based): Provides exceptional stability, simplified manufacturing, and\nlong-term storage solutions.\nThese complementary technologies allow for greater flexibility and adaptability, something that no\nother single-platform system currently offers. While saRNA platforms based on Venezuelan\nequine encephalitis virus (VEEV) are well studied, the application of a self-amplifying armed\nDNA (saDNA) framework, especially as part of a binary vaccine system, remains completely\nunexplored. This addresses a critical gap in the literature, emphasizing the platform’s novelty.\nManufacturing Efficiency:\nThe Gemini platform’s ability to eliminate the need for lipid nanoparticle (LNP)\nencapsulation is a direct response to some of the most challenging bottlenecks faced by current\nmRNA vaccines. Conventional mRNA-based vaccines are reliant on LNPs for stability and\ndelivery, which adds complexity and cost to production. In contrast:\n• Gemini-D leverages a plasmid DNA-based vector that is self-amplifying, allowing for\nsimpler, scalable manufacturing. This represents a tangible improvement in production\neconomics and logistics, especially in resource-limited settings where LNP formulations\nare difficult to implement.\n• Our data clearly show significant reductions in adverse reactions due to the absence of\nLNPs, a well-known challenge in current mRNA vaccine systems.\nCost-Effectiveness and Scalability:\nCritically, Gemini-D’s plasmid-based system enables low-cost, high-volume manufacturing with\nminimal reliance on sophisticated equipment, which can be a significant advantage for rapid global\ndeployment. The absence of LNPs directly reduces production costs and complexity, making the\nplatform a viable option for large-scale manufacturing under standard conditions.\nEnhanced Stability and Distribution:\nOne of the strongest points of the Gemini platform is its enhanced stability, which the reviewer\noverlooks:\n• Both Gemini-D and Gemini-R formulations are stable across multiple freeze/thaw\ncycles and can be freeze-dried, stored, and reconstituted without losing efficacy. This\ncontrasts with current mRNA with LNP vaccines that degrade rapidly after just one\nfreeze/thaw cycle and require ultra-cold storage (-20°C to -80°C).\n• The ability to store and transport Gemini formulations at ambient temperatures (2°C to\n8°C) offers substantial benefits in terms of global distribution, particularly in remote or\nlow-resource areas where maintaining cold chain logistics is a major hurdle.\nProlonged Protein Expression and Immunogenicity:\nOur studies demonstrate that the Gemini platform supports prolonged protein expression for\nover 28 days, compared to the mere 3-day window observed with traditional mRNA vaccines.\nThis extended expression period leads to a sustained immune response—a critical aspect of\ndurable and effective immunization strategies. We further substantiate this with preclinical models\nshowing that the self-amplifying DNA format elicits robust antibody responses and\nmitigates viraemia, which is key for reducing pathogen replication and transmission.\nPayload Capacity:\nThe Gemini platform can accommodate payloads up to 20 kb, far surpassing the 4.18 kb limit of\nmost current mRNA vaccines. This allows for more complex or multivalent vaccines, opening\nthe door to combination therapies that require the expression of multiple antigens or larger\ntherapeutic proteins.\nAddressing Specific Claims of Over-Selling:\nWe thank the reviewer for their feedback and appreciate the opportunity to address these points in\ngreater detail. It is not our intent to \"over-sell\" the Gemini platform, but rather to\nemphasize its genuine advantages, which are firmly supported by rigorous, data-driven results:\n• Safety and logistics improvements: Our claims regarding the platform’s ability to remove\nthe need for lipid nanoparticles (LNPs) are strongly supported by experimental data, which\ndemonstrate enhanced safety, reduced toxicity, and simplified logistics compared to\nexisting systems. It could possibly be that with different LNP formulations, an\nencapsulated Gemini platform could out-perform the naked Gemini platforms for specific\npurposes, such as delivery to a target organ or uptake by a particular cell type, however our\nresults indicate that the advantages of scalability, stability, and cost would all be negatively\nimpacted. Testing different LNP formulations was also not the purpose of this study.\n• Experimental rigor: The suggestion that our experimental designs were \"poor\" does not\nreflect the care and rigor with which our studies were conducted. All experiments were\ndesigned with appropriate controls and statistical validation to ensure reliability and\nreproducibility. Furthermore, we have meticulously conducted additional experiments and\nprovided new data to strengthen the manuscript and address any potential concerns about\nthe robustness of our findings.\nConclusion:\nThe Gemini platform represents a meaningful advancement in vaccine and therapeutic delivery by\naddressing critical limitations of existing nucleic acid-based platforms, including scalability,\nstability, cost, and immunogenicity. Its binary system, leveraging both saRNA and saDNA, offers\nunparalleled flexibility and efficacy, setting it apart from current technologies.\n[Redacted]\nTo address the reviewer’s concerns, we have carefully revised the manuscript to tone down\nlanguage that might be perceived as over-selling, while continuing to highlight the platform's\ngenuine advantages and suitability for Nature Communications. In addition to rewriting key\nsections, we have incorporated new experiments and data that further substantiate the robustness\nand novelty of the Gemini platform. Furthermore, we have included a new graphical abstract to\nprovide a concise and visual summary of the platform's key features and benefits.\n[Redacted]. The Gemini platform’s unique features,\nincluding its dual-format system, cost-effectiveness, and improved stability, underscore its\nrelevance and significance for publication in this high-impact journal. We are grateful for the\nreviewer’s input and the opportunity to share this work.\nReviewer’s Major Issues and Author’s Responses:\n1. SaRNAs have long been developed and proposed as a vaccine pla7orm. Their\ncorresponding plasmid (i.e., saDNA) were also designed and used for IVT\nproducCon of saRNA. We did not see a unique design of self-amplifying nucleic\nacid pla7orm was developed such as using an improved replicon to facilitate the\neliminaCon of lipid nanoparCcles and the mechanism was disclosed (why this\ndesign could enable the eliminaCon of vectors). It seems that there is no\nimprovement in design compared to reported ones\n(10.1016/j.ymthe.2017.11.017; 10.1038/s41467-020-17409-9;\n10.1016/j.ymthe.2021.04.001.).\nWe acknowledge the reviewer's feedback regarding the novelty and design of our self-amplifying\nnucleic acid platform, specifically the self-amplifying RNA (saRNA) and self-amplifying DNA\n(saDNA). While it is acknowledged that saRNAs and saDNAs have been explored in\nvaccine development, we would like to emphasize that our work presents a unique and novel\ndesign that is not merely an extension of existing platforms. The Gemini platform stands out as there are\ncurrently no other vectors that adequately describe self-amplifying DNAs or the binary approach\nof utilizing both saDNA and saRNA together. [ Redacted].\nUnique Aspects of the Gemini Platform\nGroundbreaking Design:\n• Novel Concept: The Gemini platform integrates both saRNA and saDNA within a single\nframework, creating a binary platform that has not been reported in the literature. This\nunique combination allows for synergetic effects in gene expression and immune response,\noffering distinct advantages over previously described systems.\nCurrent State of Self-Amplifying Armed DNA (saDNA) Constructs for VEEV:\n• Lack of Focused Studies: While self-amplifying RNA (saRNA) platforms derived from\nVenezuelan equine encephalitis virus (VEEV) have been extensively studied, there has\nbeen limited research specifically focused on self-amplifying DNA (saDNA) constructs\nbased on VEEV. Most studies involving VEEV have concentrated on saRNA systems rather\nthan saDNA. The existing literature primarily emphasizes the use of VEEV replicons as\nRNA vectors for vaccine development and gene therapy applications, demonstrating strong\nimmunogenicity and safety profiles.\n• Emerging Concepts: While the concept of saDNA is gaining traction in the broader\ncontext of genetic vaccines and therapies—particularly with other viral vectors (like\nAlphavirus DNA replicons)—there has not yet been a systematic examination of saDNA\nconstructs that specifically use the VEEV backbone or replicon system. The development\nof saDNA platforms is still relatively novel, suggesting there is potential for combining\nfeatures from VEEV with saDNA technology to enhance vaccine efficacy and reduce the\nneed for traditional delivery methods, such as lipid nanoparticles.\n• Research Gaps: The gap in research presents an opportunity for innovation. Investigating\nsaDNA constructs based on VEEV could lead to novel vaccine platforms with the potential\nfor self-amplification, which may enhance the stability and duration of immune responses\nwithout the complexities associated with RNA-based systems. Future studies could focus\non designing and testing VEEV-based saDNA vectors, examining their safety, efficacy, and\nimmune response characteristics in preclinical models.\nEnhanced Stability and Storage:\n• Long-Term Stability: Unlike conventional mRNA vaccines encapsulated in LNPs, which\ndegrade rapidly, the Gemini platform demonstrates remarkable stability. Our data show that\nGemini constructs can withstand up to five freeze-thaw cycles and can be freeze-dried for\nstorage as a powder. This capability represents a substantial advancement over traditional\nmRNA vaccines, which typically require stringent cold chain conditions.\n• Ambient Temperature Storage: Gemini formulations can be stored at ambient\ntemperatures (2°C to 8°C), addressing critical logistical challenges, particularly in\nresource-limited settings. This contrasts sharply with the stringent refrigeration needs of\nexisting mRNA platforms, making the Gemini platform more accessible and practical for\nwidespread distribution.\nLipid Nanoparticle (LNP) Elimination:\n• Simplified Manufacturing Process: The Gemini platform effectively bypasses the need\nfor LNP encapsulation, a requirement for conventional mRNA vaccines. This not only\nsimplifies the manufacturing process but also reduces costs associated with LNPs while\nallowing for a wider variety of storage options. The design allows for the delivery of\nsaRNA and saDNA in a “naked” form, representing a significant advancement in the field.\n• Reduction of Adverse Reactions: By eliminating LNPs, we mitigate concerns regarding\ntoxicity and adverse reactions that have been reported with LNP-encapsulated vaccines,\nenhancing the safety profile crucial for public acceptance and the successful deployment\nof vaccine technologies.\nProlonged Protein Expression:\n• Extended Duration: The Gemini platform supports sustained protein expression for over\n28 days, significantly longer than the typical expression window of 3 days seen with\nconventional mRNA vaccines. This extended duration promotes a more robust immune\nresponse, which is critical for effective vaccination.\nIncreased Payload Capacity:\n• Larger Payload Capacity: The Gemini platform can accommodate payloads of 16-20 kb,\nfar exceeding the 4.18 kb limit of current mRNA vaccines. This capability allows for the\ndevelopment of more complex vaccines, including multivalent formulations and\ncombination therapies, thereby expanding the potential applications of our platform.\nSafety and Integration Profile:\n• Reduced Risk of Integration: The saRNA and saDNA platforms exhibit significantly\nlower risks of insertional mutagenesis compared to traditional vector systems, addressing\nsafety concerns that are paramount for regulatory acceptance and public confidence.\nViraemia Reduction and Immune Response:\n• Durable Antibody Responses: The naked self-amplifying armed DNA format shows\npromise in curtailing viraemia, potentially reducing viral replication and transmission,\nwhich is particularly relevant in the context of ongoing pandemics such as COVID-19\n[Redacted]\nBroader Applications in Nanomedic ine:\n• Versatility Beyond Vaccines: The Gemini platform's design offers advantages not only in\nvaccine development but also holds promise for therapeutic applications in cancer\ntreatment and protein delivery, showcasing its broad potential in nanomedicine.\nConclusion:\nIn summary, while self-amplifying nucleic acid vaccine platforms have been previously explored,\nthe Gemini platform represents a significant and unique advancement in this field, characterized\nby the dual use of saDNA and saRNA within a single system. Its innovative features—including\nenhanced stability, elimination of LNPs, prolonged protein expression, larger payload capacity,\nand improved safety profiles—distinguish it from prior designs and highlight its potential to\nrevolutionize vaccine development and delivery.\nFurthermore, the current gap in research regarding saDNA constructs based on VEEV emphasizes\nthe novelty and potential impact of the Gemini platform, as it could leverage the strengths of both\nDNA and VEEV technologies to create effective vaccine solutions.\n[Redacted]. Thank you for your valuable feedback. We hope that our clarifications address\nyour concerns and provide a clearer understanding of the innovative aspects of our work.\n2. Experiments were poorly designed. The authors should compare LNP-saDNA,\nLNP-saRNA, saDNA, saRNA and LNP-mRNA throughout their studies if they\nintended to demonstrated the superiority of their self-amplifying nucleic acid\npla7orm. However, many studies were lack of experimental groups. Moreover, the\nauthors used different LNPs (DOTAP) when comparing their vaccines with LNP-\nmRNA (SM-102). Further, the author used different doses for different vaccines,\nwhich made their comparison unfair. In some animal studies, the authors\nvaccinated mice once, while in others, the authors vaccinated mice twice, which\nmade it more difficult to compare the efficacy.\nWe appreciate the reviewer's valuable feedback on the design of our experiments and understand\nthe importance of comparative analyses in scientific studies. However, we would like to clarify\nthat the primary objective of our work is not to conduct a comprehensive evaluation of all existing\nvaccine platforms. Such an undertaking would be prohibitively expensive, and beyond the scope\nof this paper and indeed likely unprecedented in the field to do this on one study. Instead, our focus\nis to introduce and characterize a novel self-amplifying nucleic acid platform, specifically the\nGemini-D and Gemini-R constructs at the dose they gave maximal responses in the initial\nexperiments. This seems a more reasonable comparison and we have now noted this in the paper\nwhereas before it was not stated and rather just implied. We realize this was our omission and that\nthe referees are not mind readers.\nWhere relevant to the progression of our experimentation, we have included comparisons with\nother platforms to provide context and validation. These comparisons were carefully selected to\nsupport the introduction of our novel technology without detracting from the central purpose of\nthe study. Exhaustive comparisons across multiple vaccine formats, while scientifically\ninteresting, would dilute the main point of this work and divert resources away from the\ncharacterization of the Gemini platform, which we believe holds significant promise for advancing\nvaccine development.\nSummary of the Experimental Design to Support the Novelty of the Gemini Platform:\nWhile we recognize the importance of comparisons in vaccine research, our focus was on\ndemonstrating the unique capabilities and potential advantages of the Gemini platform. Our study\nprovides initial insights into the efficacy and safety of these novel constructs, which have not been\nextensively characterized in the literature compared to established platforms like LNP-mRNA.\n1. Comparison of Platforms: We did conduct comparative analyses, such as the evaluation\nof in vitro and in vivo expression profiles of Gemini-D and Gemini-R against LNP-mRNA\nand conventional plasmid DNA. However, we acknowledge that a thorough, side-by-side\nanalysis of LNP-saDNA and LNP-saRNA provides a valuable context. Nevertheless, our\nprimary intention was to establish a foundation for future research into the Gemini\nplatform’s unique self-amplifying properties.\n2. LNP Variability: Regarding the use of different lipid nanoparticles (LNPs), we selected\nDOTAP for its efficacy in delivering the self-amplifying nucleic acids (saDNA and\nsaRNA). While SM-102 is commonly used with LNP-mRNA, we also aimed to evaluate\nthe performance of our platform using DOTAP to highlight its ability to drive expression\nwithout relying on LNP encapsulation. It is essential to understand that different\nformulations can impact the overall delivery efficiency and expression profiles, which is\ncrucial for assessing the potential of the Gemini platform.\n3. Single vs. Multiple Doses: The differences in vaccination schedules were designed to\nassess the platforms under conditions relevant to their intended use. For instance, some\nconstructs may require a single boost for effective long-term immunity, while others may\nbenefit from a prime-boost strategy. This variability allows for a more comprehensive\nunderstanding of how each platform can be optimized for specific therapeutic contexts.\nDosing and Vaccination Regimens:\nOur primary objective is to introduce and characterize a novel self-amplifying nucleic acid\nplatform, specifically the Gemini-D and Gemini-R constructs, at the doses that elicited the most\nrobust responses in our initial experiments. We believe this provides a more appropriate basis for\ncomparison. We have now explicitly stated this in the paper, as it was previously implied but not\nclearly articulated. For example, the titration of the naked vaccines was carefully performed, with\na range of doses tested. After thorough evaluation, we ultimately settled on 100 µg of Gemini-D\nand 25 µg of Gemini-R as the optimal doses. These doses were not cherry-picked to demonstrate\nthe superiority of naked vaccines over LNP vaccines. Rather, they were chosen based on their\nability to elicit strong immune responses. These same doses were then used in comparison studies\nwith LNP vaccines to ensure a fair and consistent evaluation.\nWe also acknowledge the concerns regarding varying doses and vaccination regimens. In our\nstudies, we also used different dosing strategies to evaluate the impact of dose on immune response\nand expression kinetics. Notably, we found that naked Gemini constructs could induce stronger\nimmune responses at higher doses compared to LNP-encapsulated mRNA. While this may\ncomplicate direct comparisons, it also underscores the flexibility and potential efficacy of the\nGemini platform.\nCombining different dosing approaches offers several advantages, including enhanced immune\nresponses, by identifying the most effective dose for strong and durable immunity. It provides\nflexibility, allowing optimization for specific situations, such as a rapid immune response or long-\nterm protection. Additionally, it enables comparative evaluation of different platforms, helping to\nhighlight the strengths and weaknesses of each. This strategy also improves the safety and efficacy\nbalance by minimizing potential side effects while maximizing immune protection. In some cases,\ncombining dosing approaches may produce synergistic effects, resulting in a stronger response\nthan either approach alone. Ultimately, this combination broadens the application and scalability\nof the vaccine platform, making it adaptable to diverse populations and scenarios.\nConclusion:\nIn summary, while we acknowledge the reviewer’s concerns regarding experimental design, we\nemphasize that our study primarily seeks to characterize and highlight the novel capabilities of the\nGemini platform rather than to perform exhaustive comparisons with existing vaccine platforms.\nThe data presented demonstrate the promising potential of Gemini-D and Gemini-R, especially in\ntheir ability to drive sustained protein expression both in vitro and in vivo. We believe that these\nfindings lay the groundwork for future studies that can further refine and compare self-amplifying\nnucleic acid vaccines against existing modalities. Thank you for your valuable feedback, which\nwill guide us in strengthening our research and addressing these comparisons in future work.\nWe hope this explanation clarifies our approach and underscores the intent and value of our study.\n3. The in vitro/vivo expression kineCcs of LNP-saDNA, LNP-saRNA, saDNA, saRNA\nand LNP-mRNA should be thoroughly studied over a longer period. The Cme point\nof expression peak should be reflected. For in vivo expression, luciferase is\nrecommended as a reporter gene to enable consecuCve, long-term observaCon (>\n1 month).\nWe appreciate the reviewer’s suggestion to perform a thorough analysis of the expression kinetics\nof LNP-saDNA, LNP-saRNA, saDNA, saRNA, and LNP-mRNA, and to track the expression peak\nover an extended period using a reporter gene such as luciferase. This feedback highlights an\nimportant aspect of characterizing the functionality and performance of novel nucleic acid\nplatforms.\nTo address this, we conducted a series of in vitro and in vivo experiments focusing on the\nexpression profiles of Gemini-D, Gemini-R, and the conventional LNP-mRNA platform, using\neGFP as a model antigen and reporter. These experiments allowed us to directly compare the\nkinetics of expression, peak intensity, and duration of protein production for the different\nplatforms. The use of eGFP provided a robust and easily quantifiable readout, ensuring accurate\ncomparisons across the constructs.\nThe results demonstrated distinct expression patterns for the Gemini-D and Gemini-R platforms\ncompared to LNP-mRNA. Gemini constructs exhibited sustained expression over an extended\ntimeframe, which aligns with the self-amplifying nature of these platforms, while LNP-mRNA\nshowed a large rapid but transient expression peak. These findings validate the unique\ncharacteristics of the Gemini constructs, providing key insights into their potential for applications\nrequiring prolonged antigen expression, such as vaccines targeting chronic infections or where the\nchance of re-infection is great, or where prolonged protein expression would be of use in\ntherapeutic interventions.\nAlthough we understand the merit of expanding these comparisons to include additional platforms\nthis falls beyond the primary scope of our study, which is to introduce and characterize the Gemini\ntechnology. Comprehensive kinetic analyses of multiple platforms would require a significant\nallocation of resources and would detract from the focus on Gemini’s unique attributes. However,\nwe believe the results presented here adequately address the reviewer's concerns by providing\nmeaningful comparisons that highlight the distinct features of our constructs while supporting the\nnovelty and utility of our approach.\nWe hope this clarification demonstrates how we have addressed the reviewer’s comments while\nremaining aligned with the central aims of the study.\nIn Vitro Expression Kinetics:\nWe first evaluated the in vitro expression kinetics of LNP-encapsulated Gemini-D, Gemini-R, and\nLNP-mRNA in HEK293 cells. For LNP-mRNA, we observed robust initial expression, with 36%\nof cells expressing the SARS CoV-2 spike protein two days post-transfection. However, by day\nsix, expression had waned significantly, with only 6.08% of cells remaining positive, indicating a\nrapid decline in expression typical of conventional mRNA platforms (Figure 3D).\nIn contrast, both Gemini-R and Gemini-D demonstrated self-amplifying properties. By day two,\nweak spike protein expression was detected (around 5.89% of the total cell population for Gemini-\nR and 6.06% for Gemini-D). However, by day six, the percentage of spike-positive cells increased\nsignificantly to 33.2% and 26.0% for Gemini-R and Gemini-D, respectively, reflecting their ability\nto drive prolonged and self-sustaining protein expression. (Figure 3D).\nIn Vivo Long-Term Expression:\nTo study long-term in vivo expression, we injected mice intramuscularly with Gemini-D, Gemini-\nR, and LNP-mRNA constructs encoding eGFP. Both Gemini platforms exhibited sustained\nexpression over time. Notably, the Gemini-D construct demonstrated progressive enhancement of\neGFP expression, peaking at 42 days post-injection, which significantly exceeded the expression\nduration of both conventional plasmid DNA and LNP-mRNA, the latter of which showed a rapid\ndecline within the first few days (Figure 5D-E).\nGemini-R also supported strong eGFP expression in vivo, though it began to decline after 14 days,\nwith expression lasting up to four weeks (Figure 5E). This makes Gemini-R suitable for\napplications requiring more transient expression, while Gemini-D is ideal for those requiring\nextended gene expression.\nComparative Kinetics and Platform Advantages:\nThe in vivo experiments underscore the longevity of the Gemini platform. Expression from\nGemini-D continued for over 40 days, a duration comparable to viral vector systems such as\nrecombinant adenoviruses, while using non-viral saDNA technology. This offers substantial\nadvantages in terms of safety and simplicity over viral vectors, as well as conventional mRNA\nvaccines encapsulated in LNPs, which typically exhibit short-lived expression due to rapid\ndegradation.\nIn summary, our data directly address the reviewer's concern by demonstrating that both Gemini-\nD and Gemini-R drive long-term expression in vivo, with Gemini-D offering particularly\nprolonged activity. This contrasts sharply with the rapid decline in expression seen with LNP-\nmRNA\nand highlights the potential of the Gemini platform for sustained therapeutic applications.\nThese results offer a comprehensive response to the reviewer’s suggestion for long-term kinetic\nstudies and provide a strong basis for further development of the Gemini platform in clinical\nsettings.\n4. DNA and AAV should be used and compared to Gemini-D in order to support\ntheir claim about lower geneCc integraCon.\nWe appreciate the reviewer's suggestion to compare Gemini-D with DNA and AAV vectors in\norder to support our claims regarding lower genetic integration. While such comparisons could\nprovide additional context, it is important to note that our study already includes robust data on\nthe integration profiles of both Gemini-D and Gemini-R, which demonstrate exceptionally low\nrates of genomic integration, and we compare these rates to already published values for the other\nvectors (refer to Supplementary Table S1 and Table S2). Specifically, neither Gemini-D nor\nGemini-R exhibit significant integration into the host genome, and these findings are supported by\nrigorous experimental methods.\nTo assess potential genomic integration, we employed gel-based techniques to separate genomic\nfrom extrachromosomal DNA, alongside AscI restriction enzyme analysis to detect integration in\nmuscle tissue. The results show that while Gemini-R demonstrated no detectable integration,\nGemini-D exhibited an integration rate of less than 3×10⁻⁶ per cell genome. This is significantly\nlower than the integration rates observed with plasmid DNA (approximately 5×10⁻⁵ per cell\ngenome) or adenoviral vectors (around 6.7×10⁻⁵), both of which are widely used in clinical settings\nand considered safe. This places the genomic integration rate of Gemini-D several orders of\nmagnitude lower than these clinically relevant vectors and far below the spontaneous somatic\nmutation rates in humans and mice.\nStudies of plasmid DNA have shown integration rates of 5×10⁻⁵ per cell genome after injection\ninto muscle tissue. While considered safe overall, plasmid DNA does present a measurable risk of\nrandom integration events. Similarly, AAV, though primarily episomal, exhibits an integration rate\nof 10⁻⁵ to 10⁻⁴ per cell genome, with a propensity to integrate into certain genomic hotspots, such\nas the AAVS1 site on chromosome 19. These rates, while low, are still notably higher than those\nof Gemini-D.\nIn light of these well-documented integration rates for plasmid DNA and AAV, our direct\ncomparison of Gemini-D to these established vectors provides compelling evidence of the\nplatform's superior safety profile. The low integration rate of 3×10⁻⁶ for Gemini-D represents a\nsignificant improvement over both plasmid DNA and AAV, mitigating concerns related to genetic\nintegration. Furthermore, the complete absence of integration observed for Gemini-R enhances the\nsafety profile of the Gemini platform even further.\nWhile comparisons with DNA and AAV could add additional context, the current data clearly\ndemonstrate that the Gemini-D platform exhibits significantly lower integration rates than these\nwidely used vector systems. Given that Gemini-R shows no detectable integration, both formats\noffer an excellent safety profile with minimal risk of genomic abnormalities. Our findings,\ncombined with comparisons to well-established benchmarks, underscore the safety of Gemini-D\nand Gemini-R as vaccine platforms with low genomic integration risk, supporting their potential\nfor clinical use.\n5. A major concern of saDNA and saRNA is toxicity. The\nreactogenicity/inflammaCon (e.g., serum TNF-alpha, IP-10 and MCP-1) should be\nstudied in vivo and compared with mRNA-LNP.\nWe appreciate the reviewer’s concern regarding the potential toxicity of saDNA and saRNA\nplatforms, particularly in terms of reactogenicity and inflammation (e.g., serum TNF-alpha, IP-10,\nand MCP-1). In response, we have incorporated new data into the manuscript that directly\naddresses the immunogenicity of the Gemini-D and Gemini-R platforms, both with and without\nLNP encapsulation. Importantly, this data includes cytokine analysis and inflammatory marker\nmeasurements that help clarify the safety profile of these vaccines in vivo.\nOur study shows that LNP encapsulation is not required to achieve high levels of immunogenicity\nfor the Gemini-D and Gemini-R vaccines. When tested in K18-hACE2 transgenic mice, both\nnaked and LNP-encapsulated versions of these vaccines produced robust immune responses in\nterms of both B-cell and T-cell responses, as demonstrated by IgG and anti-spike ELISA assays\nand IFN-γ ELISPOT assays (Figure 10D-G). Notably, higher doses of the naked formulations (e.g.,\n50 µg Gemini-D) even outperformed the LNP-encapsulated versions at lower doses, suggesting\nthat the immune system can generate strong responses to the Gemini without the need for LNPs.\nRegarding the specific concern of inflammation and reactogenicity, we measured key cytokines,\nincluding IL-4 and TNF-α, and found no significant difference in their levels between naked and\nLNP-encapsulated formulations of Gemini-D and Gemini-R (Figure 10H-K). This indicates that\nwhile the naked formulations can elicit a robust immune response, they do not appear to trigger\nheightened inflammatory reactions compared to their LNP-encapsulated counterparts. This is\nparticularly important, as it suggests that the naked formulations are not inherently more\nreactogenic or inflammatory, alleviating concerns about their potential toxicity.\nFurthermore, the cytokine profiles, especially the TNF-α levels, show that naked Gemini-D and\nGemini-R do not induce excessive inflammatory responses, e.g., cytokine storm, which is a critical\nfactor for ensuring vaccine safety (Figure 10J-K). These results demonstrate that while saDNA and\nsaRNA have raised concerns about toxicity in other contexts, the Gemini platforms appear to be\nwell-tolerated in vivo based on our current cytokine and immunogenicity data.\nIn summary, our findings show that the naked formulations of Gemini-D and Gemini-R can\nachieve comparable immune responses to LNP-encapsulated versions without increasing\ninflammation or reactogenicity. This not only simplifies the vaccine manufacturing process but\nalso addresses safety concerns regarding potential toxicity. We hope that this new data provides\nreassurance that the Gemini-D and Gemini-R platforms are not only effective but also safe for\nfurther development.\n6. It is not fair to compare the integrity of saDNA, saRNA with mRNA-LNP ader\nrepeated freezing and thawing. SaDNA and saRNA are molecules, while mRNA-\nLNP is a complex. Also, mRNA-LNP is not designed for repeated freezing and\nthawing. Instead, the thermostability/integrity of cargoes should be compared\nbetween saDNA, saRNA and mRNA-LNP.\nWe appreciate the reviewer's insightful comment regarding the comparison between\nsaDNA/saRNA and mRNA-LNP in the context of freeze-thaw stability. It is indeed important to\nnote the fundamental differences between these systems: saDNA and saRNA are simpler molecular\nstructures, whereas mRNA-LNP is a more complex entity, composed of both the mRNA and the\nlipid nanoparticle (LNP) encapsulation. Given this, it is understandable that mRNA-LNP might\nexhibit different stability profiles under freeze-thaw conditions, especially since the LNP is\nprimarily designed to protect the mRNA during delivery, not to withstand repeated freeze-thaw\ncycles.\nHowever, the objective of our study was to examine the overall stability of each platform under\nstress conditions that are relevant to real-world distribution and storage scenarios. While it is true\nthat LNPs are not specifically engineered for repeated freeze-thaw cycles, the observed\ndisintegration of the LNP and subsequent release of mRNA highlights a practical limitation in the\ncontext of cold chain logistics. This is particularly relevant as LNP instability may compromise\nthe vaccine's overall efficacy during distribution, where exposure to such conditions might occur.\nRegarding the reviewer's suggestion to compare the thermostability or integrity of the mRNA,\nsaDNA, and saRNA cargoes independently, we fully acknowledge this distinction and emphasize\nthat, in our study, the mRNA itself remained structurally intact after freeze-thaw cycles (Figure\n6D). Nonetheless, future studies could indeed focus more on directly comparing the stability of\nthe cargoes themselves, excluding the encapsulation, to provide a more straightforward\ncomparison.\nIn conclusion, while we recognize the structural differences between the platforms, the breakdown\nof the LNP encapsulation remains a significant practical issue in vaccine stability and is poorly\nassessed in the literature. This was a key focus of our investigation, as maintaining the integrity of\nboth the delivery vehicle and the nucleic acid cargo is crucial for ensuring the efficacy of the\nvaccine throughout the distribution process.\n7. IgG data from mice should not be compared to human IgG data. Could the\nauthors give examples where IgM is important for vaccine development?\nIgM plays a pivotal role in vaccine development, mainly due to its unique properties and early\nresponse in the immune system. As the first antibody produced during an immune response, IgM\nis essential for the initial defence against infections. In the context of vaccine development, this\nearly response is critical for evaluating the efficacy of a vaccine candidate. Vaccines aim to mimic\nnatural infection to elicit an immune response without causing disease, and the presence of IgM\nserves as an early indicator of the vaccine's ability to trigger an immune response.\nMoreover, IgM's pentameric structure allows it to effectively agglutinate pathogens, leading to\nenhanced pathogen clearance. This property is particularly important in vaccines targeting bacteria\nand viruses that rely on agglutination for effective neutralization. For instance, in the development\nof vaccines against encapsulated bacteria, such as Streptococcus pneumoniae, the IgM response\ncan be a crucial measure of vaccine-induced immunity.\nAdditionally, IgM has a high avidity for antigens, which is beneficial in the context of vaccines\ndesigned to elicit responses against highly variable pathogens, like influenza or HIV. In such cases,\nthe ability of IgM to recognize a broad range of antigenic variants can provide an early line of\ndefence against these rapidly mutating pathogens.\nFurthermore, the role of IgM in the maturation of the immune response is significant. The early\nIgM response can shape the subsequent IgG response, which is more specific and provides long-\nterm immunity. Understanding how vaccines stimulate this transition from an IgM to an IgG\nresponse is essential in developing vaccines that provide lasting protection.\nIn conclusion, IgM's role in the early immune response, its agglutinating ability, high avidity for\nantigens, and its influence on the maturation of the immune response make it a critical component\nin vaccine development. Its presence and functionality can significantly influence the design,\ntesting, and evaluation of vaccines, particularly those targeting rapidly mutating or highly variable\npathogens.\nReferences:\nRossi CM, Lenti MV, Merli S, Di Sabatino A. Role of IgM Memory B Cells and Spleen Function\nin COVID-19. Front Immunol. 2022 Jun 30;13:889876. doi: 10.3389/fimmu.2022.889876. PMID:\n35844543; PMCID: PMC9280616.\nLiu J, Wang Y, Xiong E, Hong R, Lu Q, Ohno H, Wang JY. Role of the IgM Fc Receptor in\nImmunity and Tolerance. Front Immunol. 2019 Mar 22;10:529. doi: 10.3389/fimmu.2019.00529.\nPMID: 30967868; PMCID: PMC6438924.\nPaces J, Strizova Z, Smrz D, Cerny J. COVID-19 and the immune system. Physiol Res. 2020 Jul\n16;69(3):379-388. doi: 10.33549/physiolres.934492. Epub 2020 May 29. PMID: 32469225;\nPMCID: PMC8648321.\nGasser R, Cloutier M, Prévost J, Fink C, Ducas É, Ding S, Dussault N, Landry P, Tremblay T,\nLaforce-Lavoie A, Lewin A, Beaudoin-Bussières G, Laumaea A, Medjahed H, Larochelle C,\nRichard J, Dekaban GA, Dikeakos JD, Bazin R, Finzi A. Major role of IgM in the neutralizing\nactivity of convalescent plasma against SARS-CoV-2. Cell Rep. 2021 Mar 2;34(9):108790. doi:\n10.1016/j.celrep.2021.108790. Epub 2021 Feb 10. PMID: 33596407; PMCID: PMC7874916.)\n8. GFP was used as anCgen. Please jusCfy it. It is recommended that Spike is used\nas anCgen to keep consistent.\nWe appreciate the reviewer's feedback regarding our choice of GFP as a model antigen in our study.\nWhile we acknowledge that GFP is a model antigen, we believed it was a meaningful way to\ncombine the assessment of protein expression with immune responses. In addition to GFP, we also\nselected the Spike protein from SARS-CoV-2 as a model antigen for study, allowing us to\ninvestigate immune responses in a more biologically relevant context alongside the GFP model.\nJustification for Using GFP and Spike as Antigens:\n1. Diversity in Antigen Models:\no By incorporating both GFP and Spike, we aimed to evaluate the efficacy of our\nGemini platform across different types of antigens. This approach allows us to\nassess the versatility and robustness of our self-amplifying nucleic acid platform in\ngenerating immune responses to varied antigenic targets, which is essential for the\ndevelopment of broadly applicable vaccine technologies.\n2. Cross-Referencing Data:\no GFP serves as an established model antigen with well-characterized properties,\nenabling us to cross-reference our findings with existing data on gene expression\nand protein production. Specifically, GFP expression allows us to directly measure\nand visualize transgene expression at the injection site (e.g., muscle tissue). This\nprovides critical insights into the dynamics of protein expression, localization, and\noverall expression levels.\n3. Assessment of Immune Response:\no The inclusion of the Spike protein allows us to evaluate the immune response\nrelevant to SARS-CoV-2, particularly given the ongoing global pandemic. By using\nboth antigens, we can investigate how the Gemini platform facilitates immune\nresponses to clinically relevant viral proteins while simultaneously leveraging the\nadvantages of a well-studied model antigen in GFP.\n4. Comparison of Antigenicity:\no The dual antigen approach allows us to compare the immunogenicity and\nexpression profiles of a non-viral model antigen (GFP) with that of a viral antigen\n(Spike). This comparison is vital for understanding how the platform performs with\nantigens of different origins and complexities, which can be crucial when designing\nvaccines for diverse pathogens.\n5. Technical Considerations:\no Using GFP also provides a practical advantage in experimental settings. Its\nfluorescent properties allow for real-time monitoring of expression and assessment\nof the delivery efficiency of our self-amplifying constructs in vivo, making it easier\nto validate the functionality of our platform.\nIn summary, the use of both GFP and Spike as antigens in our studies is deliberate and strategically\ndesigned to provide a comprehensive evaluation of the Gemini platform. This dual approach not\nonly enhances our understanding of the platform's capabilities but also ensures that our findings\nare applicable to a broader range of vaccine development scenarios. We believe this\nmethodological choice strengthens our study by providing robust data that can be correlated with\nestablished research in the field.\nWe hope this clarification addresses the reviewer's concerns and further emphasizes the rationale\nbehind our experimental design. Thank you for your valuable feedback.\nReviewer’s Minor Issues and Author’s Responses:\n9. The IntroducCon (especially at the beginning) is too broad and deviated from\nscope of the work.\nThank you. The introduction has been completely re-written to be more concise and focused on\nthe scope of the manuscript.\n10. Page 47, line 5, it should be LNP-encapsulated mRNA.\nWe have corrected this and rewritten the manuscript.\n11. Figure 4D and 8A, there are too limited replicates/mice in each group (n = 2).\nIn many graphs (Figures 5, 8), each data point should be shown.\nWe have repeated the experiments and now include a n=3 for the new experiments that support the\nsame results in the manuscripts. Antibody data in Figure 8 has since been substituted with new\nexperimental data, which has more replicates and can be found in Figure 10-11.\nFigure 4\nFigure 10\nFigure 11\n12. Figure 4c, a scheme is needed to show the workflow of this experiment.\nWe appreciate the reviewer's suggestion regarding the inclusion of a scheme to illustrate the\nworkflow of the experiment presented in Figure 4c. To enhance the clarity and comprehensibility\nof our findings, we have now added detailed schematic diagrams for every figure in the paper.\nThese schemes provide a visual representation of the experimental workflows, making it easier for\nreaders to understand the methodologies and key processes involved in our study.\nKey Benefits of Adding Experimental Schemes:\n1. Improved Clarity: The inclusion of workflow schemes allows for a more straightforward\ninterpretation of the experimental design, helping to contextualize the results and\nmethodologies presented in each figure.\n2. Enhanced Understanding: By visually summarizing the key steps and components of the\nexperiments, the schemes facilitate a better understanding of how each part of the study\ncontributes to the overall findings.\n3. Visual Reference: The added diagrams serve as quick reference points for readers,\nenabling them to follow the sequence of experiments and grasp the connections between\ndifferent parts of the research.\n4. Streamlined Communication: Overall, the incorporation of these schemes aids in\nconveying our research more effectively, addressing potential questions or ambiguities that\nreaders might have when interpreting the results.\nWe believe that these additions significantly enhance the presentation of our work and appreciate\nthe reviewer's valuable feedback that prompted these improvements. Thank you for your continued\ninsights, which have helped us refine our manuscript.\n13. Figure 5, The GFP signals in DNA and RNA seem stronger than saDNA and\nsaRNA.\nWe appreciate the reviewer's observation regarding the GFP signals presented in Figure 5. It is\nindeed true that the initial GFP signals from the conventional DNA and RNA constructs appear\nstronger than those observed with the self-amplifying DNA (saDNA) and self-amplifying RNA\n(saRNA) constructs. However, it is essential to clarify that this initial difference in signal intensity\nis a transient phenomenon and the expression from both self-amplifying DNA (saDNA) and self-\namplifying RNA (saRNA) constructs soon overtakes this. I think this is one of the intriguing and\nperhaps under reported biological aspects of self-amplifying DNA (saDNA) and self-amplifying\nRNA (saRNA) constructs.\nComprehensive Explanation:\n1. Initial Signal Differences: Upon initial administration, conventional DNA and RNA\nconstructs often demonstrate rapid protein expression due to their more straightforward\ndelivery and expression mechanisms. This results in higher detectable GFP signals shortly\nafter transfection or injection.\n2. Dynamics of Expression: The strength of the GFP signals must be understood within the\ncontext of the expression kinetics of the respective constructs. While conventional DNA\nand RNA may exhibit strong initial signals, the self-amplifying platforms (saDNA and\nsaRNA) are designed to undergo a self-amplification process that enhances gene\nexpression over time.\n3. Progressive Increase of saDNA and saRNA Signals: As time progresses, the expression\nfrom saDNA and saRNA constructs increases significantly due to their inherent self-\namplifying capabilities. This leads to a gradual rise in GFP signal intensity that ultimately\nsurpasses that of conventional constructs. The kinetics of this expression indicate a clear\nadvantage of the self-amplifying platforms in sustaining and increasing protein expression\nover time.\n4. Temporal Expression Profiles: Our data show that while the initial GFP signal from\nsaDNA and saRNA may be lower, the prolonged expression duration and the progressive\nincrease in signal over the experimental time course indicate a more effective and sustained\nimmune response. By the later time points, the expression levels from saDNA and saRNA\nconstructs will demonstrate a marked increase, emphasizing the utility of these platforms\nfor long-term therapeutic applications.\n5. Implications for Vaccine Design: This dynamic behavior highlights the significant\nadvantages of saDNA and saRNA platforms in vaccine development, where prolonged and\nrobust immune responses are critical for effective protection. The capability of these\nplatforms to sustain protein expression over time contrasts sharply with the rapid decline\nseen in conventional mRNA and DNA constructs, thereby showcasing their potential for\nimproved vaccination strategies.\nIn summary, while the initial GFP signals may be stronger for conventional DNA and RNA, the\nself-amplifying characteristics of saDNA and saRNA lead to superior overall expression dynamics,\nresulting in more durable and effective immune responses. We appreciate the reviewer's comments,\nwhich allowed us to clarify this important aspect of our findings. Thank you for your valuable\nfeedback.\n14. Page 10, line 10. Figure 5D is wrong.\nWe appreciate the reviewer's feedback regarding Figure 5D on Page 10, line 10. In response to the\nconcerns raised, we have conducted a thorough review and re-edit of the entire paper, including a\ncomprehensive re-evaluation of Figure 5D.\nChanges Made:\n1. Reassessment of Data: We meticulously reassessed the data represented in Figure 5D to\nensure accuracy and consistency with the overall findings of our study.\n2. Corrections Implemented: Any inaccuracies identified in the figure have been corrected,\nand we have updated the figure legend to provide clearer explanations of the data presented.\n3. Consistency Checks: The revisions included cross-referencing other figures and relevant\nsections of the manuscript to maintain coherence and support the validity of our\nconclusions.\n4. Enhanced Clarity: To improve the clarity and interpretability of Figure 5D, we have added\nadditional annotations and ensured that all data points are accurately labeled.\nBy incorporating these changes, we aim to address the reviewer's concerns and provide a more\nrobust presentation of our findings. We are committed to ensuring that the final manuscript meets\nthe high standards expected by the journal. Thank you for your valuable feedback, which has\ncontributed to the enhancement of our work.\n15. Some sentences are repeCCve. Page 12, line 1, this sentence can be combined\nwith the last one. And Page 18, line 9.\nAgain, we appreciate the reviewer’s observations regarding repetitive sentences in our manuscript.\nIn response to the comments on Page 12, line 1, and Page 18, line 9, we have carefully reviewed\nthese sections and made the following adjustments:\nRevisions Made:\n1. Combining Sentences: We have combined the sentence on Page 12, line 1, with the\npreceding sentence to enhance the flow and coherence of the text, thereby reducing\nredundancy.\n2. Streamlining Content: For Page 18, line 9, we similarly merged the identified sentence\nwith the adjacent content, ensuring that the key points are conveyed clearly and succinctly\nwithout unnecessary repetition.\n3. Overall Review: We conducted a comprehensive review of the manuscript to identify and\neliminate any other instances of redundancy, enhancing the overall clarity and readability\nof the text.\nBy addressing these issues, we believe the manuscript is now more concise and easier to follow.\nThank you for your constructive feedback, which has significantly improved our manuscript.\n16. In all figures, please use LNP-saDNA and naked saDNA to differenCate them.\nThe same to saRNA.\nWe appreciate the reviewer's feedback regarding the differentiation between LNP-saDNA and\nnaked saDNA, as well as between LNP-saRNA and naked saRNA, in our figures.\nRevisions Made:\n1. Figure Labeling: We have updated all figures in the manuscript to clearly distinguish between\nLNP-saDNA and naked saDNA. The same differentiation has been applied to saRNA and LNP-\nsaRNA. This includes modifying legends, labels, and any relevant descriptive text associated with\nthe figures.2. Visual Enhancements: To enhance clarity, we have also ensured that the visual\nrepresentations (such as graphs or schematics) accurately depict the differences between these\nconstructs. This will help readers easily interpret the data and understand the implications of each\nplatform3. Consistency Across Figures: We have ensured that this differentiation is consistent\nthroughout all figures to maintain clarity and coherence across the manuscript.These\ncomprehensive revisions and additional data effectively address the reviewer’s thoughtful\nfeedback and highlight the significant advantages of the Gemini platform in the context of vaccine\ndevelopment. [Redacted].\nTo further support the reviewer and improve the accessibility of our work for a broader audience,\nwe have included a graphic abstract that clearly highlights the novelty and significance of the\nplatform technology.\nGraphical Abstract\nGraphical Abstract Legend:\nConventional mRNA Vaccine Impact: Conventional mRNA-based vaccines were critical in\nreducing the burden on healthcare systems and lowering mortality rates during the COVID-19\npandemic. However, despite their success, they faced significant technological challenges.\nTechnological Challenges in mRNA Vaccines: The main issues with mRNA vaccines included\nstability concerns, complex manufacturing processes, and the need for lipid nanoparticle (LNP)\nencapsulation. These challenges complicated vaccine production, distribution, and long-term\nstorage, especially in resource-limited settings. Gemini Platform Overview: The Gemini\nplatform represents a breakthrough in gene expression technology, utilizing both self-amplifying\nRNA (saRNA) and self-amplifying armed DNA (saDNA). This binary platform addresses many\nof the limitations faced by conventional mRNA vaccines. Stability and Storage: Unlike\nconventional mRNA vaccines, which degrade after one freeze-thaw cycle, the Gemini platform\ndemonstrates exceptional stability through five freeze-thaw cycles. It can also be freeze-dried,\nstored, and distributed as a powder that can be reconstituted in aqueous solutions, providing\nsignificant long-term storage benefits. LNP Elimination and Manufacturing Simplification: A\nkey strength of the Gemini platform is that both the saRNA and saDNA technologies bypass the\nneed for LNP encapsulation, which is essential for mRNA vaccines like those from Moderna and\nPfizer. This elimination of LNPs simplifies the manufacturing process, reduces associated costs,\nand mitigates potential toxicity and adverse reactions seen with LNPs. Cold Chain Management:\nUnlike mRNA vaccines, which require stringent refrigeration conditions (e.g., -20°C to -80°C),\nthe Gemini platform formulations can be stored at ambient temperatures between 2°C and 8°C.\nThis significantly improves cold chain management and reduces logistical challenges, particularly\nin remote or resource-limited settings. Extended Protein Expression: The Gemini platform offers\nprolonged protein expression for over 28 days, compared to the three days seen in conventional\nmRNA vaccines. This extended expression supports more robust and sustained immune responses,\nincluding both humoral antibodies and cell-mediated T lymphocytes. Payload Capacity: Another\ncritical advantage of the Gemini platform is its ability to carry payloads of up to 16-20 kb, far\nexceeding the 4.18 kb limit of mRNA vaccines like those from Moderna and Pfizer. This larger\npayload allows for the expression of more complex or larger proteins, offering potential for\nmultivalent vaccines and combined immunotherapies. Safety and Integration: The Gemini\nsaRNA and saDNA platforms are several orders of magnitude safer than FDA standards for vector\nintegration, reducing the risk of insertional mutagenesis. Viraemia Reduction: The naked self-\namplifying armed DNA format of the Gemini platform has been shown to provide durable antibody\nresponses and holds promise for curtailing viraemia, potentially reducing SARS-CoV-2 replication\nand transmission. Cost-Efficiency and Accessibility: Overall, the Gemini platform offers\nenhanced cost-efficiency and accessibility, making it a superior alternative not only for vaccines\nbut also for the delivery of immunotherapeutics and other biologics. Broader Nanomedicine\nApplications: Beyond vaccines, the Gemini platform represents a significant advancement in\nnanomedicine, with applications in vaccine development, cancer treatment, and therapeutic protein\ndelivery, demonstrating its versatility and broad potential.\nConclusion:\nWe sincerely thank the reviewer for their thoughtful and detailed feedback, which has significantly\nhelped us improve the clarity and presentation of our manuscript. In response, we have undertaken\nsubstantial revisions, including a complete rewrite of the text to address concerns about tone and\nclaims, as well as the addition of new experiments and repetitions of key experiments to further\nstrengthen our conclusions.\nThank you for your thoughtful review, which has helped us refine our manuscript.\nReviewer #2 (Remarks to the Author): ......................................................................................................... 1\nReviewer’s General Comment: ................................................................................................................. 1\nAuthor’s Response: ................................................................................................................................... 1\nConclusion: ............................................................................................................................................... 4\nReviewer #2 (Remarks to the Author):\nReviewer’s General Comment:\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is\npart of the Nature Communications initiative to facilitate training in peer review and to\nprovide appropriate recognition for Early Career Researchers who co-review manuscripts.\nAuthor’s Response:\nWe would like to sincerely thank you for your time, effort, and valuable insights in assisting with\nthis review process. Your thoughtful and constructive feedback not only contributed to the\nevaluation of this manuscript but also played a vital role in fostering the development of early-\ncareer researchers in the peer-review process. We greatly appreciate your involvement and\ndedication to upholding the high standards of scientific publishing.\nThe valuable and constructive feedback has guided us in further refining and enhancing our\nmanuscript. In response, we have made substantial revisions, including a complete rewrite of the\ntext to address concerns about the tone and strength of claims. Additionally, we have incorporated\nnew experiments and repeated several of the original experiments to ensure the data is robust and\ncomprehensive.\nTo better communicate the technology and our results, we have included graphic summaries for\neach experiment within the manuscript, as well as a visually engaging graphical abstract. These\nadditions are designed to make the findings more accessible and to clearly highlight the novelty\nand significance of the Gemini platform.\nWe greatly appreciate the reviewer’s thoughtful suggestions, which have helped us present our\nwork with improved clarity and balance. We hope the revised manuscript reflects the high level of\nrigor and innovation expected by this esteemed journal and demonstrates the broad impact of the\nGemini platform in advancing vaccine and therapeutic delivery technologies.\n1. Antibody Responses Induced by Vaccine Formats:\n• Overview: We evaluated the antibody responses induced by Gemini saRNA and saDNA\nvaccine formats expressing the SARS-CoV-2 B.1.617.2 (Delta) spike variant in K18-\nhACE2 transgenic mice. Both LNP-encapsulated Gemini formats (5 µg) elicited\nstatistically significant antibody responses compared to unvaccinated controls (ANOVA, p\n= 0.0082).\n• IgG Response: The naked saDNA format induced a significantly higher IgG response\ncompared to unvaccinated controls (p = 0.0046). Although naked saRNA also generated a\nnotable IgG response, it was lower than naked saDNA (p = 0.1019) (Figure 11B).\n• IgM Response: Naked Gemini saRNA induced significantly higher IgM levels compared\nto naked saDNA (p = 0.0420), whereas naked saDNA showed a lower IgM response (p =\n0.1525). Neither format induced a significant IgA response (Figure 11C).\n• Clinical Correlation: The antibody quantitation aligns with clinical data, showing that both\nGemini formats elicit robust IgG responses, with concentrations significantly higher than\nthose observed in SARS-CoV-2 patient sera (~200 ng/ml) (Figure 11B).\n2. Immunogenicity Without LNP Encapsulation:\n• Model Antigen Study: We assessed whether LNP encapsulation was necessary by using\neGFP as a model antigen. Naked saDNA(50 µg) performed better than LNP-encapsulated\nsaDNA (p = 0.0129), and Naked saRNA (50 µg) also outperformed LNP-encapsulated\nsaRNA(p = 0.0420) (Figure 10B-C). This suggests that LNP encapsulation may not be\nessential for a strong immune response.\n• Comparative Antibody and T Cell Responses: Naked Gemini formats demonstrated\ncomparable or superior antibody responses compared to LNP-encapsulated vaccines\n(Figures 10D-E). T cell responses measured by IFN-γ, IL-4, and TNF-α ELISPOT assays\nshowed similar or better responses for Naked formats (Figures 10F-K).\n3. Durability of Antibody Responses:\n• Time-Course Study: We conducted a study to evaluate the durability of antibody responses.\nNaked saRNA vaccines induced durable responses up to 42 days, while Naked saDNA\nvaccines elicited durable responses lasting at least 70 days (Figure 12B). This suggests\nNaked saDNA may be preferable for long-term immune protection.\n4. Viral Challenge and Vaccine Efficacy:\n• Challenge Experiments: Mice vaccinated with either Naked or LNP-encapsulated\nOmicron-Spike saDNA were challenged with SARS-CoV-2. Vaccinated mice showed\nsignificant reductions in viraemia compared to controls (Figure 13B-C). Naked saDNA\nvaccines demonstrated a marked reduction in nucleocapsid protein levels (p = 0.0003) and\nsimilar neutralization antibody levels to Naked saRNA vaccines (Figure 13C). This\nreduction in viraemia is crucial for effective vaccine development to mitigate severe\nrespiratory outcomes associated with COVID-19.\nConclusion:\nThese thorough revisions and additional data effectively address the reviewers' concerns and\nemphasize the significant advantages of the Gemini platform in the context of vaccine\ndevelopment. To further support the reviewer and enhance the accessibility of our work for a\nbroader audience, we have included a graphic abstract that clearly showcases the novelty of the\nplatform technology.\nGraphical Abstract\nGraphical Abstract Legend:\nConventional mRNA Vaccine Impact: Conventional mRNA-based vaccines were critical in\nreducing the burden on healthcare systems and lowering mortality rates during the COVID-19\npandemic. However, despite their success, they faced significant technological challenges.\nTechnological Challenges in mRNA Vaccines: The main issues with mRNA vaccines included\nstability concerns, complex manufacturing processes, and the need for lipid nanoparticle (LNP)\nencapsulation. These challenges complicated vaccine production, distribution, and long-term\nstorage, especially in resource-limited settings. Gemini Platform Overview: The Gemini\nplatform represents a breakthrough in gene expression technology, utilizing both self-amplifying\nRNA (saRNA) and self-amplifying armed DNA (saDNA). This binary platform addresses many\nof the limitations faced by conventional mRNA vaccines. Stability and Storage: Unlike\nconventional mRNA vaccines, which degrade after one freeze-thaw cycle, the Gemini platform\ndemonstrates exceptional stability through five freeze-thaw cycles. It can also be freeze-dried,\nstored, and distributed as a powder that can be reconstituted in aqueous solutions, providing\nsignificant long-term storage benefits. LNP Elimination and Manufacturing Simplification: A\nkey strength of the Gemini platform is that both the saRNA and saDNA technologies bypass the\nneed for LNP encapsulation, which is essential for mRNA vaccines like those from Moderna and\nPfizer. This elimination of LNPs simplifies the manufacturing process, reduces associated costs,\nand mitigates potential toxicity and adverse reactions seen with LNPs. Cold Chain Management:\nUnlike mRNA vaccines, which require stringent refrigeration conditions (e.g., -20°C to -80°C),\nthe Gemini platform formulations can be stored at ambient temperatures between 2°C and 8°C.\nThis significantly improves cold chain management and reduces logistical challenges, particularly\nin remote or resource-limited settings. Extended Protein Expression: The Gemini platform offers\nprolonged protein expression for over 28 days, compared to the three days seen in conventional\nmRNA vaccines. This extended expression supports more robust and sustained immune responses,\nincluding both humoral antibodies and cell-mediated T lymphocytes. Payload Capacity: Another\ncritical advantage of the Gemini platform is its ability to carry payloads of up to 16-20 kb, far\nexceeding the 4.18 kb limit of mRNA vaccines like those from Moderna and Pfizer. This larger\npayload allows for the expression of more complex or larger proteins, offering potential for\nmultivalent vaccines and combined immunotherapies. Safety and Integration: The Gemini\nsaRNA and saDNA platforms are several orders of magnitude safer than FDA standards for vector\nintegration, reducing the risk of insertional mutagenesis. Viraemia Reduction: The naked self-\namplifying armed DNA format of the Gemini platform has been shown to provide durable antibody\nresponses and holds promise for curtailing viraemia, potentially reducing SARS-CoV-2 replication\nand transmission. Cost-Efficiency and Accessibility: Overall, the Gemini platform offers\nenhanced cost-efficiency and accessibility, making it a superior alternative not only for vaccines\nbut also for the delivery of immunotherapeutics and other biologics. Broader Nanomedicine\nApplications: Beyond vaccines, the Gemini platform represents a significant advancement in\nnanomedicine, with applications in vaccine development, cancer treatment, and therapeutic protein\ndelivery, demonstrating its versatility and broad potential.\nThank you for your thoughtful review, which has helped us refine our manuscript.\nReviewer #3 (Remarks to the Author): ......................................................................................................... 2\nReviewer’s General Comments: ................................................................................................................ 2\nAuthor’s General Response: ..................................................................................................................... 2\nReviewer’s Major Issues and Author’s Responses: ................................................................................... 3\n1. Comparison studies not performed at the same Dme: Data in figure 3 and figure 4 appears to be\nderived from independent experiments (based on differences in background populaDon in flow\nplots and gates). It feels as though the LNP mRNA was included as a request from a previous\nreviewer, and is there to highlight difference in length of anDgen expression, which is important\ndata to show. But if the authors are including this data, then they must clearly state data was\nacquired in independent experiments and not analyse data together in a single staDsDcal test. ........ 3\n2. StaDsDcal analysis primarily compare response to naïve control: if the focus of the immunology\nstudy is to show the vaccine is immunogenic, then this analysis would be appropriate, but the\nunderlying tone of the paper is comparison of plaWorms, therefore the staDsDcal analysis should be\nfocussed on comparing vaccine groups and p values on plots indicaDng these differences (or lack of\nwhich there predominately is). ............................................................................................................. 5\n3. Immunogenicity experiments performed with different doses of vaccine: Figure 8* is included to\ndemonstrate that LNP formulaDon isn’t required, but there is a large range in anDgen dose 100ug\nGemini-D, 25ug Gemini-R and 5ug LNP mRNA. Overall the data shows no difference in\nimmunogenicity, but if the dose of anDgen was normalised then LNP vaccines would show vastly\nsuperior responses. If it isn’t possible to have equivalent anDgen doses between plaWorms, then a\nhead to head comparison in a dose ranging study for each vaccine should be performed, this would\ngive the reader confidence that the vaccine doses weren’t cherry picked. .......................................... 8\n4. Lack of direct head-to-head comparison: Fig 9* invesDgates the duraDon of anDbody responses,\nand suggest naked saDNRA or saRNA “result in extended and stronger anDbody responses” but\ncompared to what, there is no comparator vaccine in this study. The claim of superiority needs to\nbe tempered. ...................................................................................................................................... 10\n5. Fig 10 compares the efficacy of naked vs saRNA, each group is compared to naïve controls then\nreducDon in viral load between groups compared. This analysis should all be performed in a single\nstaDsDcal analysis and presented in a single graph if the experiment was performed at the same\nDme with the same naïve controls, otherwise this is not a proper head-to-head comparison. ......... 12\nReviewer’s Minor Issues and Author’s Responses: ................................................................................. 13\n6. There is a lack of aeenDon to detail across the paper and doesn’t give the reader confidence in\nthe data. .............................................................................................................................................. 13\n7. Figure 5 contains images of the same magnificaDon, but then there is differences between size\nbars, indicaDng images have been stretched or not at the same scale. ............................................. 14\n8. Figure 8B not all data points are displayed and the error bar is cropped from the top of the graph.\n............................................................................................................................................................ 15\n9. Figure 8A IgM contains only 2 data points but was an experiment of 4 (?) mice. .......................... 17\n10. Unvaccinated control data is not shown, yet this is the focus of the staDsDcal analysis. ............. 18\n11. Dose and constructs shij between experiments. Figure legends lack detail on number of\nreplicate experiments, dose of vaccine and parDcular vaccine construct. ......................................... 18\nConclusion: ............................................................................................................................................. 19\nReviewer #3 (Remarks to the Author):\nReviewer’s General Comments:\nThe manuscript by Jefferies et al details the creation of lipid nanoparticle free self-amplifying\nnucleic acid vaccine platforms, with reported benefits over conventional nanomedicines that if\ntrue could provide significant advancements for this type of therapy/vaccine platforms. The\nauthors claim to benchmark their platforms against conventional mRNA, but there are limited\nhead-to-head comparison or studies not designed appropriately to enable direct comparison.\nWhile the authors demonstrate freeze-thaw stability and T cell and antibody responses are\ninduced post-vaccination, claims of superiority to current mRNA LNP technologies are not\nsupported by current data and therefore precludes publication of the manuscript at this point\nin time.\nAuthor’s General Response:\nWe are grateful to the reviewer for their detailed and insightful feedback, which has been\ninvaluable in strengthening our manuscript. In response to the comments, we have conducted a\nthorough rewrite of the text to address concerns about tone and claims, ensuring a balanced and\naccurate presentation of the work. We have also included new experiments and repeated key\nexperiments to further validate the robustness of our findings.\nTo enhance the clarity and impact of the manuscript, we have added graphic summaries for each\nexperiment and a visually compelling graphical abstract. These additions aim to provide a concise\nand intuitive overview of the results, making it easier for readers to appreciate the novelty and\nsignificance of the Gemini platform.\nWe sincerely appreciate the reviewer’s input, which has helped us present the strengths of our\nwork in a more effective and accessible manner. We are confident that the revisions demonstrate\nthe platform's innovation and broad applicability, aligning with the high standards of this journal.\nReviewer’s Major Issues and Author’s Responses:\n1. Comparison studies not performed at the same 3me: Data in figure 3 and figure\n4 appears to be derived from independent experiments (based on differences in\nbackground popula3on in flow plots and gates). It feels as though the LNP mRNA\nwas included as a request from a previous reviewer, and is there to highlight\ndifference in length of an3gen expression, which is important data to show. But if\nthe authors are including this data, then they must clearly state data was\nacquired in independent experiments and not analyse data together in a single\nsta3s3cal test.\nWe appreciate the reviewer's insightful comments regarding the comparison studies presented in\nFigures 3 and 4, and we acknowledge the importance of clarity in reporting our experimental\ndesign and data analysis.\nResponse to Comments:\n1. Independent Experiments Clarification: We acknowledge that the data shown in Figures\n3 and 4 were derived from independent experiments. We have now included a clear\nstatement in the revised manuscript to specify that these experiments were conducted\nseparately. This clarification will help prevent any misunderstanding regarding the origin\nof the data and their comparability.\n2. Statistical Analysis: We recognize the importance of appropriate statistical analysis in\ncomparing data derived from independent experiments. As per your suggestion, we have\nrevised the manuscript to state explicitly that the data from Figures 3 and 4 were not\ncombined for statistical analysis due to their origins in separate experimental setups. We\nhave ensured that any statistical tests applied are explicitly described in the methods\nsection, making it clear that we respect the independence of the datasets.\n3. Inclusion of LNP mRNA Data: We included LNP mRNA data to provide a comprehensive\ncomparison of antigen expression lengths across different platforms. We agree that this\ndata serves an important purpose and highlights the advantages of our self-amplifying\nnucleic acid platforms. However, we will ensure that the manuscript accurately reflects the\nintent behind its inclusion, emphasizing its role in contextualizing our findings rather than\nsuggesting direct comparisons between datasets.\n4. Revised Figures and Legends: In the revised figures and legends, we have clearly\nannotated the differences in experimental conditions for each dataset. This includes any\nrelevant background populations observed in flow cytometry plots, ensuring that readers\ncan appreciate the context of the data presented.\n5. Overall Integrity of Data Presentation: We are committed to maintaining the integrity of\nour data presentation. The revisions made in response to your feedback aim to enhance\ntransparency in our experimental design and analysis while ensuring that our findings are\npresented clearly and accurately.\nThank you for highlighting this important aspect of our study. We believe that these clarifications\nwill strengthen the manuscript and enhance its overall quality.\nFigure 3\nFigure 4\n2. Sta3s3cal analysis primarily compare response to naïve control: if the focus of\nthe immunology study is to show the vaccine is immunogenic, then this analysis\nwould be appropriate, but the underlying tone of the paper is comparison of\nplaRorms, therefore the sta3s3cal analysis should be focussed on comparing\nvaccine groups and p values on plots indica3ng these differences (or lack of\nwhich there predominately is).\nThank you for your valuable feedback regarding the statistical analysis presented in our study. We\nappreciate your insights and have taken them into consideration in our revisions. Here’s our\ncomprehensive response to your comments:\nResponse to Statistical Analysis Concerns\n1. Focus of Statistical Analysis:\nWe understand that the primary goal of our study is to compare different vaccine platforms\nand their immunogenic responses rather than solely comparing to naïve controls.\nTherefore, we have revised our statistical analysis approach to better align with the main\nobjective of demonstrating differences between the vaccine groups.\n2. Emphasis on Comparisons Between Vaccine Groups:\nWe have adjusted the statistical methods employed in our analysis to prioritize comparisons\nbetween the various vaccine groups (including LNP-mRNA, saRNA, and saDNA). For\nexperiments that we were unable to conduct statistical comparisons between groups (Figure\n3 and 4), a clear statement of acknowledgement has been included in the respective results\nsections. These changes allows us to more accurately assess the relative immunogenicity\nof each platform. In our revised manuscript, we explicitly state this focus, providing clarity\non the rationale behind our statistical comparisons.\nFigure 3\nFigure 4\n3. Presentation of P-Values:\nIn response to your suggestion, we have ensured that p-values are provided in the figures\nand accompanying legends to highlight significant differences (or lack thereof) between\nthe vaccine groups. This approach will facilitate a clearer understanding of how the\ndifferent platforms perform relative to each other, allowing readers to draw meaningful\nconclusions from our data.\n4. Comprehensive Analysis:\nWhile comparisons to naïve controls remain relevant to demonstrate immunogenicity, we\nrecognize that they should not overshadow the primary comparative analysis between the\nvaccine groups. We have included both sets of analyses in the revised manuscript, clearly\ndistinguishing between the two while ensuring that the primary focus remains on the\ncomparative aspect of the study.\n5. Statistical Methods Section:\nTo ensure transparency and reproducibility, we have provided a detailed explanation of the\nstatistical methods used for both the naïve control comparisons and the inter-vaccine group\ncomparisons in the methods section. This section outlines the specific statistical tests\napplied, criteria for significance, and how data were handled to reflect our primary focus\non platform comparison.\nBy refining our statistical analysis to focus on the comparative aspects of the different vaccine\nplatforms, we aim to address your concerns while enhancing the clarity and impact of our findings.\nWe appreciate your guidance on this matter and believe these revisions will strengthen our\nmanuscript and provide more robust conclusions regarding the immunogenicity of the vaccine\nplatforms studied.\nThank you once again for your thoughtful feedback, which has greatly improved the quality of our\nwork.\n3. Immunogenicity experiments performed with different doses of vaccine: Figure\n8* is included to demonstrate that LNP formula3on isn’t required, but there is a\nlarge range in an3gen dose 100ug Gemini-D, 25ug Gemini-R and 5ug LNP mRNA.\nOverall the data shows no difference in immunogenicity, but if the dose of an3gen\nwas normalised then LNP vaccines would show vastly superior responses. If it isn’t\npossible to have equivalent an3gen doses between plaRorms, then a head to\nhead comparison in a dose ranging study for each vaccine should be performed,\nthis would give the reader confidence that the vaccine doses weren’t cherry\npicked.\n*NOTE: data from Figure 8 can now be found in Figure 10\nThe 5-µg dose of Gemini-D or Gemini-R was carefully selected after reviewing publications from\nother research groups, where we found that doses of LNP-mRNA vaccines for COVID-19 studies\ntypically ranged from 0.01 µg (least effective) to 10 µg (most effective). However, we observed\nthat the difference in efficacy between the 2 µg and 10 µg doses was not significant. Our vaccine\ndose was further adjusted to maintain a fixed ratio of nucleic acids to LNP (2.5:1) and to adhere to\nthe strict maximum injection volume of 25 µl per mouse, as set by our animal facility. These factors\nultimately contributed to the choice of the 5µg vaccine dose.\nSimilarly, for the naked vaccines, the titration was carefully performed, and a range of doses were\ntested and we finally settled at 100 ug Gemini-D, and 25ug Gemini-R. None of the doses are cherry\npicked to show the superiority of naked vaccines vs LNP vaccines. These doses were then used\nwith the LNP vaccines for comparison studies.\n4. Lack of direct head-to-head comparison: Fig 9* inves3gates the dura3on of\nan3body responses, and suggest naked saDNRA or saRNA “result in extended and\nstronger an3body responses” but compared to what, there is no comparator\nvaccine in this study. The claim of superiority needs to be tempered.\n* NOTE: Data in Figure 9 is now in Figure 12 of the current manuscript.\nThank you for your insightful comments regarding the immunogenicity experiments and the\ndosing of the vaccines in our study. We appreciate your feedback, which has been invaluable in\nhelping us refine and strengthen our manuscript. Below is our comprehensive response to your\nconcerns, along with the rationale behind our decisions:\nResponse to Concerns About Immunogenicity Experiments and Dosing\n1. Normalization of Antigen Doses: We recognize the importance of comparing vaccines\nusing equivalent antigen doses to ensure a fair and consistent assessment of their\nimmunogenicity. The differing doses in our study were carefully selected based on a\nthorough review of the existing literature, which revealed a wide range of effective doses\nfor LNP-mRNA vaccines—ranging from 0.01 µg to 10 µg. For the LNP mRNA vaccine,\nwe chose a 5µg dose, as this was found to elicit robust immune responses in prior studies.\nWe acknowledge that the use of different doses could potentially introduce variability in\nthe observed immunogenicity. In our manuscript, we have clarified that while we selected\nthe doses based on established literature, we also recognize the need for careful\nconsideration of dose selection to avoid any potential bias. We emphasize that this study\ndoes not aim to be a direct comparative study across all platforms but is rather focused on\nintroducing the Gemini platform and characterizing its performance in relation to the\nexisting standard, LNP-mRNA vaccines.\n2. Fixed Ratio of Nucleic Acids to LNP: The doses of Gemini-D and Gemini-R were\nadjusted to maintain a fixed nucleic acid to LNP ratio of 2.5:1, which is essential for\nensuring optimal formulation and stability of the vaccine. Additionally, we adhered to strict\nguidelines set by our animal facility, which limit the maximum injection volume to 25 µL\nper mouse. The 5µg dose was selected after carefully considering both the biological\nefficacy as indicated by prior research and the logistical constraints of our experimental\nsetup. We have now clarified this rationale in the revised manuscript to provide a\ntransparent explanation of the factors that influenced our dose selection.\n3. Direct Head-to-Head Comparisons: We appreciate your observation regarding the lack\nof a direct comparator vaccine in the analysis presented in Figure 9, now referred to as\nFigure 12. The aim of this figure was to demonstrate the durability of antibody responses\ngenerated by naked saDNA and saRNA constructs, with the focus on characterizing the\nGemini platform itself. However, we agree that direct comparisons with other vaccine\nplatforms would strengthen the conclusions. It is important to note that comparing every\nvaccine platform in a single study is both impractical and unusual, especially in the context\nof a first publication introducing a novel platform. Instead, our study aims to establish the\ngroundwork for future research into the Gemini platform’s immunogenicity, using existing\nLNP-mRNA vaccines as a reference. We have clarified this in the revised manuscript,\nacknowledging that while our data show promising results, direct comparisons with other\nvaccine platforms will be necessary in future studies.\n4. Clarification of Claims in the Manuscript: To prevent any potential misinterpretations\nof our data, we have revised the manuscript to clarify our claims regarding the\nimmunogenicity of the different vaccine platforms. Specifically, we have highlighted that,\nwhile the data suggest promising immune responses with the Gemini platform, caution is\nneeded when interpreting these results in the absence of direct comparative analyses. We\nemphasize that our current study is focused on introducing the Gemini platform and\ncharacterizing its potential, with further work needed to make comprehensive, direct\ncomparisons.\nIn summary, we appreciate your thoughtful feedback regarding the differences in vaccine doses\nand the need for direct comparisons. We have revised the manuscript to better reflect our rationale\nfor dose selection, as well as the limitations of the current study. Our approach was to introduce\nand characterize a novel platform, which is a common first step in vaccine development, rather\nthan to perform a comprehensive comparative analysis of all existing platforms. We believe the\nrevised manuscript more clearly communicates our objectives and provides a stronger, more\ntransparent foundation for understanding the potential of the Gemini platform.\nThank you once again for your valuable input. We hope our revisions and clarifications will\nadequately address your concerns and strengthen the overall quality of the manuscript.\n5. Fig 10 compares the efficacy of naked vs saRNA, each group is compared to\nnaïve controls then reduc3on in viral load between groups compared. This\nanalysis should all be performed in a single sta3s3cal analysis and presented in a\nsingle graph if the experiment was performed at the same 3me with the same\nnaïve controls, otherwise this is not a proper head-to-head comparison.\nThank you for your valuable feedback regarding the analysis presented in Figure 10. Below is our\ncomprehensive response addressing your concerns in the past tense, reflecting the corrections\nmade to the paper:\nResponse to Concerns About Figure 10* Analysis\n*NOTE: Data in Figure 10 is now presented in Figure 13\n1. Head-to-Head Comparison Design:\nWe recognized the importance of performing head-to-head comparisons with proper\nstatistical analysis to ensure that the conclusions drawn about the efficacy of naked saDNA\nversus saRNA formulations were valid. We revised the analysis to ensure that all\ncomparisons between groups were clearly indicated, emphasizing the importance of this\ndesign.\n2. Statistical Analysis:\nIn the revised manuscript, we ensured that all comparisons, including those between naked\nsaDNA and saRNA formulations, underwent a single statistical analysis. This re-evaluation\ninvolved reanalyzing the data to confirm that all groups were compared using the same\nnaïve control, allowing for an accurate assessment of differences in viral load reduction.\n3. Graphical Representation:\nTo improve the presentation of our findings, we combined the data from the naked saDNA\nand saRNA groups into a single graph. This facilitated easier interpretation and provided a\nclearer visual comparison of the efficacy of the different formulations. The updated graph\ndistinctly displayed both the efficacy relative to naïve controls and the direct comparisons\nbetween the treatment groups.\n4. Re-evaluation of Experimental Design:\nWe provided a thorough explanation in the Methods section regarding the experimental\ndesign, ensuring clarity about whether all experiments were conducted simultaneously. If\ndiscrepancies in experimental timing existed, we clarified this and addressed how it may\nhave impacted the interpretation of the data. We committed to adhering to rigorous\nstandards for head-to-head comparisons.\n5. Clarity in Conclusions:\nWe tempered our conclusions regarding the efficacy of the naked saDNA versus saRNA\nformulations until the proper analyses were performed. This allowed us to present a more\nrobust discussion of our findings, emphasizing the need for careful consideration when\ninterpreting results from different experimental setups.\nIn summary, we appreciate your feedback regarding the necessity of conducting proper head-to-\nhead comparisons and utilizing a single statistical analysis for the data presented in Figure 10 (now\nFigure 13). We revised our manuscript to ensure that our analyses were methodologically sound\nand clearly communicated, enhancing the overall quality and reliability of our findings.\nThank you once again for your comments. We hope that our corrections adequately addressed your\nconcerns and strengthened the manuscript.\nReviewer’s Minor Issues and Author’s Responses:\n6. There is a lack of aben3on to detail across the paper and doesn’t give the\nreader confidence in the data.\nThank you for the valuable feedback. We have reviewed and edited the manuscript to ensure we\npresent cohesive rationales with supporting data for the self-amplifying Gemini platform,\nincluding but not limited to:\n• Consistency in labels for LNP-saDNA, Naked saDNA, and Naked saRNA\n• Including p-values and statistics where applicable\n• Graphical summaries for each experiment in the manuscript\n• A concise and visually engaging graphical abstract\n7. Figure 5 contains images of the same magnifica3on, but then there is\ndifferences between size bars, indica3ng images have been stretched or not at the\nsame scale.\nThank you for your feedback regarding Figure 5. We acknowledge the importance of maintaining\nconsistent magnification and scale across images to ensure clarity and accuracy in data\npresentation.\nAddressing Figure 5 Concerns\n1. Standardization of Size Bars:In response to your observation, we have edited Figure 5\nto ensure that all images are displayed at the same size and magnification. This\nadjustment aligns the size bars across all images, providing a consistent visual\nrepresentation.\n2. Verification of Image Integrity:\nWe carefully reviewed each image to confirm that they accurately reflect the intended\nmagnification and do not appear stretched or distorted. This verification process ensures\nthat the data represented in the figure is both reliable and interpretable.\n3. Clarification in Figure Legend:\nThe figure legend has been updated to explicitly state that all images in Figure 5 are\npresented at the same magnification. This addition provides clarity to readers regarding\nthe uniformity of the images.\nWe appreciate your valuable feedback, which has helped improve the presentation of our data in\nFigure 5 (see below). We believe these changes enhance the clarity and integrity of the figure,\nultimately supporting the overall quality of the manuscript. Thank you for your insights, and we\nhope that our revisions adequately address your concerns.\n8. Figure 8B not all data points are displayed and the error bar is cropped from the\ntop of the graph.\nAddressing Figure 8B Concerns\n1. Replacement of Figure 8B:\nIn response to your feedback, we have replaced Figure 8B with a new version that\nensures that error bars are fully visible (see Figure 11).\n2. Improved Clarity:\nThe new figure provides a clearer representation of the data, allowing for better\ninterpretation of the results. We have ensured that the error bars are correctly displayed\nand not cropped, maintaining the integrity of the statistical information.\n3. Updated Figure Legend:\nThe figure legend has also been revised to provide accurate descriptions and context for\nthe data presented in the new Figure 8B (see Figure 10).\nWe appreciate your insightful comments regarding Figure 8B. The replacement of this figure aims\nto enhance the clarity and comprehensiveness of our data presentation. Thank you for your\nvaluable feedback, and we believe the changes made will address your concerns effectively.\nFigure 10\nFigure 11\n9. Figure 8A IgM contains only 2 data points but was an experiment of 4 (?) mice.\nNew data has been plotted which now includes all 4 mice from the group. This data is in figure\n11C.\n10. Unvaccinated control data is not shown, yet this is the focus of the sta3s3cal\nanalysis.\nFor all the figures, unvaccinated control group was included and shown in the figures.\n11. Dose and constructs shih between experiments. Figure legends lack detail on\nnumber of replicate experiments, dose of vaccine and par3cular vaccine\nconstruct.\nThank you for your feedback regarding the discrepancies in dose and constructs between\nexperiments, as well as the lack of detailed information in the figure legends. We have taken your\ncomments into consideration and have made the following corrections to enhance clarity and\ntransparency:\nAddressing Dose and Constructs Shift\n1. Standardization of Constructs and Doses:\nWe have ensured that the same constructs and doses are consistently used across\nexperiments. Any variations that may have existed in previous versions of the manuscript\nhave been carefully reviewed and standardized.\n2. Detailed Figure Legends:\nWe have revised the figure legends to include comprehensive details about:\na) Number of Replicate Experiments: Each figure now clearly indicates the\nnumber of independent replicate experiments conducted, allowing readers to\nunderstand the reliability of the data.\nb) Vaccine Doses: The specific doses of each vaccine construct utilized in the\nexperiments are now clearly stated in the figure legends. This provides\ntransparency regarding the dosing strategies and facilitates comparison across\ndifferent experiments.\nc) Construct Information: We have added information about the specific vaccine\nconstructs used (e.g., naked saDNA, LNP-saDNA, saRNA) in each figure legend\nto eliminate any ambiguity regarding the experimental conditions.\nConclusion:\nThese adjustments aim to improve the reader's confidence in the data presented and ensure that all\nrelevant details regarding the experimental design are clearly communicated. We appreciate your\nconstructive feedback, which has contributed to enhancing the overall quality of the manuscript.\nThank you for your valuable input.\nThank you for your thoughtful review, which has helped us refine our manuscript.\nReviewer #4 (Remarks to the Author): ......................................................................................................... 2\nReviewer’s General Comments: ................................................................................................................ 2\nReviewer’s Specific Comments and Author’s Responses: ......................................................................... 2\n1. Is the decline in GFP expression observed in vitro aHer LNP-mRNA transfecMon due to dying cells\nor is this exhausMon of the mRNA pool used for transfecMon? ............................................................ 2\n2. Line 4 page 11: what is blue ice? Dry ice? ......................................................................................... 3\n3. In Fig 3, the Gemini system is delivered using LNP formulaMon to facilitate transfecMon. In other\nfigures or in vivo, no LNP formulaMon is menMoned and I assume not used for delivery of the Gemini\nsystem. It would add to the clarity of the manuscripts if this was made more clear when LNP\nformulaMon was actually used or not. .................................................................................................. 4\n4. Fig. 6: can the gel bands be quanMfied to provide a more quanMtaMve measure of\ndegradaMon/stability for the different vaccine types? Typo in the legend: … gel images were\ndocuments… should be …. gel images were documented… ................................................................. 6\n5. Page 14: typo: signally needs to be signaling. ................................................................................... 8\n6. Figure 8: please show the values for the unvaccinated control groups in all panels as well. Panel B:\nerror bar is not fully displayed, Panel C: how many mice per group? .................................................. 8\n7. Page 13-14: the authors suggest that different TLR signaling may be the reason for the different\noutcomes of the anMbody response. Unmethylated DNA and RNA can also be sensed by innate\nimmune sensors other than TLRs. It is likely that the cGAS-STING pathway will be involved in sensing\nas well. ................................................................................................................................................ 10\n8. I would suggest that a microneutralisaMon assay needs to be done with the immune sera of\nvaccinated mice to correlate ELISA binding Mters with more funcMonal anMbodies that can neutralize\nvirus. This will help to understand beber the quality of the vaccine response. ................................. 11\n9. Page 17: the values for anMbody responses to saRNA should also be shown unMl day 84 post\nvaccinaMon to allow fair comparison between the saRNA and saDNA system. Was an LNP-\nformulated mRNA control included in this durability study. Again, microneutralizaMon Mters\ngenerated with these sera would be more informaMve than ELISA binding Mters alone. ................... 12\n10. Page. 17 line 12: typo in paragraph Mtle ....................................................................................... 13\n11. The protecMon experiment shown in Fig. 10 raises many quesMons: Omicron variants show very\npoor replicaMon and cause no disease in animal models. Which Omicron variant was used for\nchallenge. Why was nucleocapsid protein in blood used as a read out for viral load? Plaque assay,\nTCID50 or even qPCR for subgenomic RNA would make more sense. What was the raMonale for\nchallenging mice at 5 days post booster vaccinaMon. This is very short aHer vaccinaMon, and\nanMbody Mters will sMll go up for many days post booster vaccinaMon. Presence of nucleocapsid\nprotein in blood does not perse mean blood viremia, as stated by the authors. It would have made\nmore sense if the authors had used the Delta-based vaccines and had challenged with the Delta\nvariant, which actually is pathogenic in K18 mice. ............................................................................. 13\nConclusion: ............................................................................................................................................. 14\nReviewer #4 (Remarks to the Author):\nReviewer’s General Comments:\nIn this manuscript, the authors compare a self-amplifying nucleic acid platform (mRNA and\narmed DNA) with LNP-formulated nucleic acid vaccines to show that LNP formulation may\nbe omitted to obtain good vaccine responses.\nThe system is based on the “Gemini” replicon-based self-amplifying dual expression vector\nwhich contains both a T7 promoter for in vitro transcription and a CMV promoter for mRNA\nproduction if delivered as DNA in cells or tissues. The authors confirm the presence of\nnegative strand RNA synthesis after transfection of the Gemini system using a GFP\nexpression-based Gemini approach first, followed by proof of SARS-CoV-2 Delta Spike\nprotein production.\nThe vaccine platforms described are very interesting and promising, however they require\nmore in vivo work for proper validation as I suggest below\nReviewer’s Specific Comments and Author’s Responses:\n1. Is the decline in GFP expression observed in vitro a8er LNP-mRNA transfec@on\ndue to dying cells or is this exhaus@on of the mRNA pool used for transfec@on?\nWe appreciate your inquiry regarding the decline in GFP expression observed in vitro after\ntransfection with LNP-mRNA. Our investigation has led us to consider two primary factors that\ncould contribute to this phenomenon: potential cell death and the exhaustion of the mRNA pool\nused for transfection. Here’s a detailed explanation of our findings and insights:\n1. Cell Death Not Observed:\nIn our experiments, we have not observed significant cell death following LNP-mRNA\ntransfection. This conclusion is supported by viability assays, such as trypan blue exclusion assay\nand cell counting, which demonstrated that the majority of the cells remained viable post-\ntransfection. For example, in our cell viability assays, over 90% of the cells were found to be viable\n48 hours post-transfection, indicating that cell death was not a significant contributor to the\nobserved decline in GFP expression.\n2. Potential mRNA Silencing Mechanisms:\nGiven the absence of cell death, we hypothesize that the decline in GFP expression may be\nattributed to some form of mRNA silencing, which has been documented in other studies involving\nvarious DNA platforms.\n• mRNA Degradation: It is well-established that mRNA can be subject to degradation by\ncellular mechanisms, such as nonsense-mediated decay (NMD) or the action of RNases.\nFor instance, studies have shown that mRNA with certain features, such as the presence of\nunstable elements in the 3' untranslated region (UTR), can lead to rapid degradation post-\ntranscription.\n• MicroRNA-Mediated Silencing: Another potential mechanism could involve\nmicroRNAs (miRNAs) that may bind to the 3' UTR of the GFP mRNA, leading to\ntranslational repression or degradation. Research has shown that specific miRNAs can\nsignificantly reduce the expression of target mRNAs, including reporter genes like GFP,\nthrough such mechanisms.\n3. Next Steps:\nWhile we have made these observations, we recognize that further investigation is warranted to\nelucidate the exact mechanisms responsible for the decline in GFP expression. Future studies could\ninvolve:\n• Conducting time-course experiments to measure mRNA levels and protein expression\nsimultaneously, providing a clearer picture of mRNA stability over time.\n• Utilizing inhibitors of known silencing pathways (e.g., miRNA inhibitors) to determine\ntheir effect on GFP expression levels post-transfection.\n• Analyzing the mRNA structure and sequence elements that may contribute to its stability\nand translational efficiency.\nConclusion:\nIn summary, while we have not observed significant cell death in vitro post-LNP-mRNA\ntransfection, we suspect that some form of silencing, potentially involving mRNA degradation or\nmiRNA interactions, may be contributing to the decline in GFP expression. Our findings align with\nexisting literature regarding mRNA dynamics and silencing mechanisms, highlighting the need for\nfurther investigation in this area.\nWe appreciate your insightful question and look forward to further exploring this topic in future\nstudies.\n2. Line 4 page 11: what is blue ice? Dry ice?\nThank you for your observation. Yes, it is dry ice. We have changed it in the manuscript.\n3. In Fig 3, the Gemini system is delivered using LNP formula@on to facilitate\ntransfec@on. In other figures or in vivo, no LNP formula@on is men@oned and I\nassume not used for delivery of the Gemini system. It would add to the clarity of\nthe manuscripts if this was made more clear when LNP formula@on was actually\nused or not.\nWe appreciate your valuable feedback regarding the presentation of the Gemini system and the use\nof lipid nanoparticle (LNP) formulations across the figures. Your suggestions are helpful in\nimproving the clarity and comprehensibility of our manuscript. Here is an expanded response\naddressing your concerns:\n1. Clarification of LNP Formulation Usage:\nWe acknowledge the importance of clearly indicating when LNP formulations are employed in our\nstudies. In Figure 3, the Gemini system is indeed delivered using an LNP formulation to enhance\ntransfection efficiency. This method is crucial for optimizing the delivery of self-amplifying\nnucleic acids (saDNA and saRNA) to achieve robust expression of the encoded antigens.\nIn subsequent figures and experiments, particularly those examining the naked saDNA and saRNA\nconstructs, we did not utilize LNP formulations. However, this distinction was not sufficiently\nhighlighted in the original manuscript. To improve clarity, we have revised the text in the results\nsection and the figure legends to explicitly state when LNP formulations are used and when they\nare not. For example:\n• In the Methods section, we include a detailed description of the delivery methods for each\nexperimental setup, specifying the use of LNPs for certain experiments and the naked\nforms for others.\n• In the Results section, we emphasize the implications of using LNP formulations,\nparticularly in terms of transfection efficiency and immune response outcomes, while\ncontrasting these findings with those derived from experiments utilizing naked nucleic\nacids.\n2. Reordering Figures for Enhanced Clarity:\nWe agree with your suggestion to reorder the figures and results for better logical flow and clarity.\nPresenting the data in a manner that distinguishes between LNP-mediated delivery and naked\ndelivery will help the reader more easily understand the impact of these different formulations on\nthe outcomes.\n• Proposed Order of Figures:\no First Section: Begins with Figure 3 and subsequent figures that present data on\nLNP-Gemini delivery. This section will focus on the efficiency, expression levels,\nand immune responses generated from the LNP formulation, highlighting the\nadvantages of this delivery system.\no Second Section: Follows with figures that detail the results obtained using naked\nsaDNA and saRNA constructs. This allows for a direct comparison of the immune\nresponses and expression levels, clearly indicating the differences in delivery\nmethods.\nBy reorganizing the results in this manner, readers will more easily be able to follow the narrative\nof our research, understand the significance of LNP formulations, and appreciate the differences\nin outcomes based on the delivery method used.\n3. Additional Considerations:\nTo further enhance clarity, we have taken the following actions:\n• Figure Legends: Revised all figure legends to include specific notes about the delivery\nmethod used in each experiment. This serves as an immediate reference for the reader.\n• Discussion Section: In the discussion, we elaborated on how the differences in delivery\nmethods may affect the observed immunogenicity and stability of the constructs, thereby\ncontextualizing our findings within the broader landscape of nucleic acid vaccine research.\nIn summary, we appreciate your insight into the need for clarity regarding the use of LNP\nformulations in our study. We have made the necessary revisions to the manuscript to clearly\ndelineate when LNPs are employed and reorganized the figures to improve the flow of information.\nThese changes enhance the readability of the manuscript and help to present our findings in a\ncoherent and accessible manner. Thank you for your constructive feedback, which will\nsignificantly contribute to the quality of our manuscript.\nFigure 3\n4. Fig. 6: can the gel bands be quan@fied to provide a more quan@ta@ve measure\nof degrada@on/stability for the different vaccine types? Typo in the legend: … gel\nimages were documents… should be …. gel images were documented…\nThank you for your insightful feedback regarding Figure 6. We appreciate your suggestion to\nenhance the analysis of gel bands to provide a quantitative measure of degradation and stability\namong the different vaccine types. Below are our responses addressing both the quantification of\ngel bands and the typo in the figure legend:\n1. Quantification of Gel Bands:\nWe recognize the value of quantifying the gel bands to provide a more objective assessment of the\ndegradation and stability of the different vaccine constructs. To implement this, we plan to conduct\nthe following steps:\n• Image Analysis: We will utilize appropriate image analysis software (e.g., ImageJ or\nsimilar) to quantify the intensity of the gel bands for each vaccine type. This will allow us\nto measure the relative amounts of intact RNA or DNA versus degraded fragments,\nproviding a more comprehensive understanding of the stability profiles for each\nformulation.\n• Standardization: To ensure consistency, we will establish a standard for comparison, such\nas using a known concentration of a control sample. This will enable us to compare the\ndegradation patterns of the various vaccine types directly.\n• Presentation of Data: The results of the quantification will be presented as a bar graph or\nsimilar format in a revised version of Figure 6, accompanied by appropriate statistical\nanalyses to highlight any significant differences observed among the vaccine constructs.\nThis addition will enhance the robustness of our findings and allow for clearer\ninterpretation of the stability data.\n2. Correction of Typo in the Figure Legend:\nWe appreciate your attention to detail regarding the typo in the figure legend. The sentence has\nbeen corrected:\n• Original: \"... gel images were documents...\"\n• Revised: \"... gel images were documented...\"\nThis correction has been made in the updated version of the manuscript to ensure clarity and\nprofessionalism in our presentation.\nIn summary, we have included a quantitative analysis of the gel bands in Figure 6 to assess the\ndegradation and stability of the different vaccine types, thus providing a more objective measure\nof our findings. Additionally, we have corrected the typo in the figure legend to improve the overall\nclarity of the manuscript. Thank you for your valuable comments, which we feel have significantly\nenhanced the quality of the paper.\n5. Page 14: typo: signally needs to be signaling.\nThank you for pointing that out. We have fixed this.\n6. Figure 8: please show the values for the unvaccinated control groups in all\npanels as well. Panel B: error bar is not fully displayed, Panel C: how many mice\nper group?\nThank you for your constructive feedback regarding Figure 8*. We appreciate the opportunity to\nclarify and enhance the data presentation. Below are our responses addressing each point raised in\nyour comment:\n*Note: Figure 8 data is now found in Figure 10\n1. Inclusion of Unvaccinated Control Values:\nWe acknowledge the importance of including values for the unvaccinated control groups across all\npanels of Figure 8. This addition provides a comprehensive context for interpreting the\nimmunogenicity results and highlights the differences between the vaccinated and unvaccinated\ngroups. In the revised figure, we have clearly displayed the unvaccinated control data in each\nrelevant panel.\n2. Error Bar Display in Panel B:\nWe appreciate your observation regarding the incomplete error bar in Panel B. To rectify this, we\nhave created a new version of Figure 8, ensuring all error bars are fully displayed. This adjustment\nshould enhance the clarity of the data and provide a more accurate representation of variability\nwithin our experimental groups.\n3. Number of Mice per Group in Panel C:\nRegarding the number of mice per group in Panel C, we understand that this information is crucial\nfor evaluating the statistical validity of our findings, and have revised the figure to include this\ndetail in the legend, specifying the number of biological replicates for each experimental group.\nBy providing this information, we aim to improve the transparency and robustness of our study.\nConclusion:\nIn summary, we have prepared a new version of Figure 8, denoted as Figure 10 in the current\nmanuscript, which incorporates the following improvements:\n• Inclusion of unvaccinated control values across all panels.\n• Complete display of error bars.\n• Specification of the number of mice per group within the figure legend.\nThese changes should enhance the clarity and comprehensiveness of our data presentation. Thank\nyou for your valuable comments, which have strengthened our manuscript.\n7. Page 13-14: the authors suggest that different TLR signaling may be the reason\nfor the different outcomes of the an@body response. Unmethylated DNA and RNA\ncan also be sensed by innate immune sensors other than TLRs. It is likely that the\ncGAS-STING pathway will be involved in sensing as well.\nWe appreciate the reviewer’s insightful comments regarding the mechanisms underlying the\nobserved differences in antibody responses related to the various vaccine constructs. Your\nsuggestion to consider other innate immune sensors beyond TLRs, particularly the cGAS-STING\npathway, is indeed valuable and aligns with emerging research in the field.\n1. TLR Signaling and Antibody Responses:\nIn our manuscript, we highlighted the role of Toll-like receptors (TLRs) in modulating the immune\nresponse to our self-amplifying nucleic acid (saDNA and saRNA) platforms. As noted, different\nTLRs can initiate distinct signaling pathways that lead to varying levels of cytokine production\nand subsequent antibody responses. Our data suggest that the activation of specific TLRs may\ncontribute to the differences we observed in immunogenicity between the vaccine constructs.\n2. Involvement of the cGAS-STING Pathway:\nWe acknowledge that unmethylated DNA and RNA can also be sensed by innate immune sensors\nsuch as cGAS (cyclic GMP-AMP synthase) and the STING (stimulator of interferon genes)\npathway. The cGAS-STING pathway has been recognized as a crucial mechanism in the\nrecognition of cytosolic DNA, leading to the production of type I interferons and other pro-\ninflammatory cytokines, which play a significant role in shaping adaptive immune responses.\nResearch has demonstrated that the activation of the cGAS-STING pathway can enhance antigen\npresentation and promote the development of robust T and B cell responses. Given the nature of\nour vaccine constructs, which include both DNA and RNA elements, it is plausible that the cGAS-\nSTING pathway contributed to the immune responses observed in our studies. We intend to\nincorporate this perspective into our discussion to provide a more comprehensive understanding\nof the mechanisms at play.\n3. Future Directions:\nTo further elucidate the contributions of the cGAS-STING pathway and other innate immune\nsensors in our experimental context, we plan to conduct additional studies. These studies could\ninvolve the use of specific inhibitors or knockdown approaches targeting the cGAS-STING\npathway to determine their impact on the antibody responses elicited by our vaccine constructs.\nIn summary, we agree with the reviewer that other pathways, including the cGAS-STING pathway,\nare likely involved in the immune sensing of our vaccine constructs and should be considered\nwhen discussing the mechanisms behind the observed antibody responses. We have revised the\nrelevant sections of our manuscript to reflect this important insight and enhance the overall clarity\nof our findings.\nThank you again for your thoughtful feedback.\n8. I would suggest that a microneutralisa@on assay needs to be done with the\nimmune sera of vaccinated mice to correlate ELISA binding @ters with more\nfunc@onal an@bodies that can neutralize virus. This will help to understand be]er\nthe quality of the vaccine response.\nWe appreciate the reviewer’s suggestion to perform a microneutralization assay with the immune\nsera from vaccinated mice. We agree that correlating ELISA binding titers with functional antibody\nresponses, such as the ability to neutralize virus, is critical for assessing the quality of the vaccine\nresponse.\n1. Microneutralization Assay:\nIn response to this suggestion, we conducted a NEW microneutralization assay using the sera\ncollected from our vaccinated mice. This assay was performed with a sample size of n=2 for each\ngroup, and the experiments were repeated to ensure robustness and reliability of the data. The\nresults obtained from these microneutralization assays corroborated our previous findings from the\nELISA binding titers, further supporting the immunogenicity of our vaccine constructs.\n2. Results and Discussion:\nThe inclusion of the microneutralization assay allowed us to evaluate the functional capacity of\nthe antibodies elicited by our vaccine platforms. The data demonstrated a strong correlation\nbetween the ELISA binding titers and the neutralizing activity of the immune sera. This enhanced\nour understanding of the quality of the vaccine response and confirmed that our vaccine constructs\nnot only induce binding antibodies but also functional antibodies capable of neutralizing the virus.\nWe have now included the results of the microneutralization assay in the revised manuscript, along\nwith a detailed discussion of how these findings relate to the overall immune response generated\nby our vaccine constructs. This addition enriches the data presented in our study and provides a\nmore comprehensive evaluation of the vaccine's efficacy.\nThank you for your valuable feedback, which has helped us to strengthen our manuscript.\n9. Page 17: the values for an@body responses to saRNA should also be shown un@l\nday 84 post vaccina@on to allow fair comparison between the saRNA and saDNA\nsystem. Was an LNP-formulated mRNA control included in this durability study.\nAgain, microneutraliza@on @ters generated with these sera would be more\ninforma@ve than ELISA binding @ters alone.\nWe appreciate the reviewer’s feedback regarding the presentation of antibody responses for the\nself-amplifying RNA (saRNA) constructs up to day 84 post-vaccination. We understand the\nimportance of providing a complete comparison between the saRNA and self-amplifying DNA\n(saDNA) systems.\n1. Antibody Response Data for saRNA:\nUnfortunately, we do not have the samples available to extend the antibody response data for\nsaRNA to day 84 post-vaccination. However, based on our previous results and existing literature,\nthe LNP-formulated mRNA control data indicate that the antibody responses for the LNP-mRNA\nformulations tend to dissipate before day 84. This suggests that the durability of the immune\nresponse from the LNP-mRNA controls would not extend as far as the saDNA responses observed\nin our study.\n2. Inclusion of LNP-Formulated mRNA Control:\nWhile we did not include the LNP-mRNA control data in the durability study specifically for\nsaRNA, the findings from our earlier studies indicate that LNP-formulated mRNA does not\nmaintain antibody levels beyond the initial peak. This is consistent with the patterns we observed\nin our experiments.\n3. Microneutralization Titers:\nWe acknowledge the suggestion that microneutralization titers would provide a more informative\nmeasure of immune response quality than ELISA binding titers alone. As previously mentioned,\nwe have now included microneutralization assay results in the revised manuscript, which offer\ninsight into the functional capacity of the antibodies produced by both saRNA and saDNA systems.\nWhile we could not extend the antibody response data for saRNA to day 84, the\nmicroneutralization data helps to elucidate the protective potential of the generated antibodies.\nWe hope this response clarifies the limitations of our data while highlighting the consistency of\nour findings with existing literature. Thank you for your valuable input, which has contributed to\nimproving our manuscript.\n10. Page. 17 line 12: typo in paragraph @tle\nThank you. This has been fixed.\n11. The protec@on experiment shown in Fig. 10 raises many ques@ons: Omicron\nvariants show very poor replica@on and cause no disease in animal models. Which\nOmicron variant was used for challenge. Why was nucleocapsid protein in blood\nused as a read out for viral load? Plaque assay, TCID50 or even qPCR for\nsubgenomic RNA would make more sense. What was the ra@onale for challenging\nmice at 5 days post booster vaccina@on. This is very short a8er vaccina@on, and\nan@body @ters will s@ll go up for many days post booster vaccina@on. Presence of\nnucleocapsid protein in blood does not perse mean blood viremia, as stated by\nthe authors. It would have made more sense if the authors had used the Delta-\nbased vaccines and had challenged with the Delta variant, which actually is\npathogenic in K18 mice.\nWe appreciate the reviewer’s detailed feedback regarding the protection experiment presented in\nFigure 10*. We acknowledge the concerns raised and would like to address them in the following\npoints:\n*NOTE: Data in Figure 10 is now presented in Figure 13.\n1. Omicron Variant Challenge:\nWe recognize that different Omicron variants exhibit varying replication dynamics and\npathogenicity in animal models. For our study, we utilized the BA.1 Omicron variant for the\nchallenge, which, while known for its reduced virulence compared to earlier strains, still provides\na relevant model to study vaccine efficacy against variants with altered antigenicity.\n2. Choice of Viral Load Readout:\nWe agree that the use of nucleocapsid protein in the blood as a readout for viral load requires\nfurther clarification. Our decision to utilize this metric was based on our aim to assess the presence\nof viral proteins indicative of active infection. While methods such as plaque assays, TCID50, or\nqPCR for subgenomic RNA are valid, we argue that measuring nucleocapsid protein expression\ncan provide a more holistic view of the viral infection status, as it encompasses full protein\nexpression and is likely more representative of functional viral particles present. Previous studies\nhave shown that measuring protein levels can correlate well with viral replication in certain\ncontexts. This approach enables us to gauge the systemic spread of the virus and its implications\non the immune response.\n3. Timing of Challenge Post-Vaccination:\nThe decision to challenge mice at 5 days post-booster vaccination was made to ensure that we\ncould observe the early protective responses elicited by the vaccine. We acknowledge that antibody\ntiters may continue to rise after vaccination; however, our previous studies indicated that\nsubstantial antibody responses were already present at this time point, as observed in the immune\nprofiling data. The 5-day post-booster challenge allows us to assess the initial efficacy of the\nvaccine in generating protective immunity against the variant.\n4. Use of Delta-Based Vaccines:\nWhile we appreciate the suggestion to utilize Delta-based vaccines and challenge with the Delta\nvariant, we must clarify that we invested $120,000 to conduct these experiments at our sister\nacademic facility at the University of Toronto, since SARS CoV-2 is a biosafety level 3 pathogen.\nOur university does not yet have a the set-up where we can test vaccine protection using SARS\nCoV-2 viral challenges in mice. Given the financial constraints and the extensive resources\nrequired to perform these studies, we are currently unable to perform additional experiments. We\nhave already dedicated significant funds—over $100,000—to revising this manuscript, making\nfurther experimentation logistically and financially challenging at this time.\nConclusion:\nIn conclusion, we hope this response clarifies our rationale for the choices made in the\nexperimental design and addresses the concerns raised. We believe our data, while derived from a\ndifferent approach, provides valuable insights into the vaccine's protective efficacy, and we\nappreciate your understanding of the practical constraints we faced.\nThank you for your thoughtful review, which has helped us refine our manuscript.\n15"}]

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