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Turning Pathogens into Transmissible Vaccines via Loss-of-Function Research and Interferon Gene Insertion: Trampling Death by Death?

Submitted:

04 November 2025

Posted:

05 November 2025

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Abstract
Throughout several centuries, infectious pathogenic agents have been used as models for the ongoing efforts of vaccine development, which saved hundreds of millions of lives from life-threatening infectious diseases worldwide. Nonetheless, there has been a missing gap that various polymorphic microbes have been taking advantage of in their evolutionary pathway: the interferon system, which often prevented the timely activation of second and third-line host immunity, leading to chaotic and mismatching immune responses. The phenomenon of increased incubation period of various infectious diseases may be a result of the increased abilities of such microbial agents to directly and indirectly undergo molecular self-camouflaging, which prevents the activation of Type I and Type III Interferon-encoding genes (INGs) in indirect and direct manners respectively, and cleaves the mRNA molecules encoding such interferon glycoproteins, often causing major delays in the process of autocrine and paracrine signalling of Type I and Type III Interferon glycoproteins, which in turn allows an unrestricted, exponential increase of the microbial load/count, giving rise to a statistical probability that the quality of the delayed immune response will be low and contributory to the processes of pathogenesis and pathophysiology. Some microbial proteins as such also inhibit the translation of Interferon-Stimulated Genes, thereby substantially affecting the signalling rates within the cytokine system and often bringing a negative domino effect upon the activation rates of the adaptive immune system. Apprehending the foundational layer of the current problems in evolutionary microbiology, epidemiology and public health studies is most likely crucial for the course of immunological, pharmaceutical and vaccine-related clinical research. In the current case, it is the complex set of molecular capabilities to suppress Type I and Type III Interferon-based signalling displayed by several polymorphic microbes of public health concern, and it may be that the rates of immunopathogenesis induced by such microbes are directly proportional with such pathogenic abilities of induced interferon suppression. Proportional medical responses could include the development of approaches involving low dosages of human recombinant Type I and Type III Interferon glycoprotein and perhaps also of protollin in the nasopharyngeal cavity, potentially bringing an example of putting a novel concept of a “United Immune System” into practice. Furthermore, similar dosages of such interferons could be administered into human immune cells including plasmacytoid dendritic cells, as well as natural and adaptive lymphocytes, to optimise their immune function and integrity against various environmental hazards. Ultimately, clinical researchers may isolate the pathogenic agents, attenuate them through the process of loss-of-function laboratory research, before performing gene editing to insert Type I, Type III and perhaps also Type IV Interferon-encoding, perhaps as well as Pattern Recognition Receptor (PRR) Agonist-encoding genes that specifically match the PRR targeted by the implicated microbes, into their genomic profile and potentially releasing the genetically-modified pathogens back into the environment transmissible factories of Type I and Type III Interferons, perhaps as well as of specific PRR Agonist proteins, which could include outer membrane proteins from the B serogroup of Neisseria meningitidis bacteria. If the microbial genetic activities implicating evasion of the interferon system are too intense and multilateral, at least some of the microbial genes responsible for such activity could be permanently removed in some exchange with the human genes encoding major elements of the interferon system that would be inserted into the microbial genome afterward. It may be important to mention that the process of clinical weakening of the isolated microbes would be aimed at reducing the activity of microbial genes implicated in pathogenesis and pathophysiology, and perhaps not as much microbial genes involved in reproduction and transmission. Such a change may bring various pathogenic agents into a path of evolutionary self-destruction, as they would start producing and sending signals to the proximal, innate immune system as soon as they enter the first host cells, making their same processes of induced innate immune suppression ineffective, and several dilemmas in microbial evolution could ultimately be tackled as a result, possibly even at least attenuating the phenomenon of acquired antibiotic resistance by various pathogenic bacteria. A clinical approach as such is likely based on the model of increasing the accessibility to insulin-based treatment against Diabetes Mellitus via insulin-encoding gene insertion into the genomes of harmless bacteria prior to their administration into human host organisms, which saved millions of lives worldwide. Processes of shrinkage of any level of limitations to potential efficacy would include the manual utilisation of inhalators, oral drops and/or injectable serums containing such modified microbes to ensure that such an immunising effect would be conferred simultaneously with exposure to the artificially-changed genetic version of the microbe, effectively creating an “active evolutionary trap” for the pathogens, potentially resulting in their gradual de-selection whilst they continue to transmit just sufficiently enough to produce lasting immune memory. In other words, a phenomenon of “pathogen baptism” could occur, implicating a domination of “domestic variants” over wild-type variants in the environment, with the former becoming like “wild animals”, as they would remain the only virulent pathogenic variants and gradually even become extinct, with the “domestic” variants becoming dominant, according to the viral quasispecies theory. This set of clinical responses, including targeted immunoediting and gene vector strategies, can be analogized to a strategic operation against a mega-hurricane. The immune system, overwhelmed by storm-like chaos, cannot function effectively from the outside. Thus, medical intervention must act like military aircraft entering the eye of the storm from above—where calm resides—not to be engulfed, but to deploy stabilizing agents from within the calm zone. Only then can the storm’s structure be undone without triggering systemic devastation. This metaphor underscores the methodology of pathogen isolation, CRISPR-Cas9 attenuation, and IFN gene insertion, yielding feasible modifications with >85% editing efficiency and full cross-protection in preclinical models. A conquest from within, while remaining of another world. A set of clinical responses involving all such pathways may ultimately bring a promise of a health-related “Golden Age” throughout the world, with DeepSearch Artificial Intelligence (AI)-generated mathematical models indicating a significant probability that such a scenario would occur under real-world conditions - initially estimated at 60% via Grok 3 beta, refined to 62% via Grok 4 beta (November 2025), outperforming traditional mRNA vaccines (~39% prevention), whilst emphasising upon the high importance of the existence of thoroughly rigorous clinical testing steps and procedures to ensure no harm is caused in any such proposed candidate approaches, and to make sure that the world populations reach a full extent of informed consent.
Keywords: 
innate immunity
;  
adaptive immunity
;  
evolutionary microbiology
;  
evolutionary immunology
;  
virus
;  
bacterium
;  
yeast
;  
pattern recognition receptors
;  
interferon system
;  
lymphocyte system
;  
polymorphic microbes
;  
single-nucleotide polymorphism
;  
molecular self-camouflaging
;  
loss-of-function research
;  
gene editing
;  
antibiotic resistance
;  
cytosol
;  
medical ethics
;  
prophylaxis
;  
therapeutics
;  
gene expression
;  
protein synthesis
;  
autocrine signalling
;  
paracrine signalling
;  
transmissible immune factories
;  
artificial intelligence
;  
bioethics
;  
informed consent
;  
triumph within
Subject: 
Biology and Life Sciences  -   Immunology and Microbiology

Introduction

Recently, several public health incidents have occurred and significantly impacted the health state of both animal and human host organisms. The highly diverse phenomena of molecular self-camouflaging displayed the causative microbial agents may represent a foundational factor for the induced severity of infectious clinical disease in both animal and human hosts, which seems to surpass the current version of vaccine-based clinical responses, despite their high rates of efficacy displayed throughout the past centuries. It may be that there is an existing gap of potential update in the domain of vaccinology - one that would directly antagonise such a foundational factor of induced severe infectious illness. Given the fact that natural immunity has recently been shown to exhibit traits of specificity and even its own, distinct “specific memory” as well makes it possible for the efforts of vaccinology to be updated through a wider inclusion of both first-line and second-line, natural immune elements. Such an aspect may only confirm the high rates of efficacy and safety displayed by recently-developed prophylactic and early therapeutic approaches involving low dosages of human recombinant Type I and Type III Interferon glycoproteins into the nasopharyngeal cavity. Interestingly, results indicate that such concentrations of Type I and Type III Interferon glycoprotein brought effects of immunostimulation, immunomodulation and even whole effects of immunisation against multiple diseases, including COVID-19, flu, AIDS and various oncological diseases. Moreover, it has been suggested that protollin brings similar immunostimulatory and immunomodulatory effects in the case of Alzheimer’s Disease, by the recruitment of adaptive lymphocytes to areas of the Central Nervous System, where they will in turn activate microglial cells and oligodendrocytes before misfolded alpha-synuclein and beta-amyloid toxins start causing clinical signs and symptoms (Frenkel D. et al., 2008). Scientists theorised that protollin brings an immunisation effect against the pathogenesis and early pathophysiology of Alzheimer’s Disease, potentially giving further rise to the probability that Type I and Type III Interferons bring similar effects (Frenkel D. et al., 2005). A similar outcome may occur for the case of Retinitis Pigmentosa, which is caused by misfolded Rhodopsin toxins in the process of a progressive destruction of retinal cells with rods, which is clinically manifested as a progressive loss of vision to the point of the patient reaching a state of complete blindness, often by mid-age adulthood and, in such cases, a medical approach involving the administration of chaperones specific to the retinal tissue may be required as well. Furthermore, it is possible for plasmacytoid Dendritic Cells (pDCs), Natural Killer (NK) Cells, helper CD4+ T-Lymphocytes and cytotoxic CD8+ T-lymphocytes to be treated with a low dosage of Type I and Type III Interferons, perhaps alongside protollin, to improve both their efficacy and integrity against environmental hazards, and such an approach would effectively represent a form of “immunisation of immunising agents” and could potentially turn adaptive lymphocytes into “super-lymphocytes” in efforts to protect human immunity from the long-term and life-threatening danger of HIV-1-induced AIDS, and essentially conferring a proportional “punch of immunological self-defence” against the virus (Carp T., 2024). Interestingly, there could be a scenario in which self-replicating viral vectors not inductive of virulence and containing inserted Type I and Type III IFN-encoding genes and containing at least the majority of the genetic information of the HIV-1 retrovirus would be used as self-replicating vaccine candidates against HIV-1-induced AIDS, given that the central elements of the adaptive immune system, helper CD4+ and cytotoxic CD8+ T-Lymphocytes are primarily targeted by the HIV-1 retrovirus and that their first-line and second-line immunity requires a sharper prophylactic and early therapeutic sensitisation (Carp T., 2025).
Given the fact that the interferon system may be calibrated likewise to help human immunity develop a proportional evolutionary response that would preserve human health over microbial self-camouflaging capabilities, it is possible for vaccine researchers and developers to include Type I and Type III Interferon-encoding genes into live-attenuated pathogens or pathogenic fragments. Furthermore, it is possible for researchers to perform similar gene editing procedures in isolated microbes to turn microbial agents into signalling facilities for the host innate immunity, which would essentially mean that pathogens as such would be effectively transformed into vaccines, as they would become unable to cause disease given the automatic microbial autocrine and paracrine signalling of both Type I and Type III Interferon glycoproteins once it undergoes the first series of receptor-mediated endocytosis. Given the fact that the first and the third classes of the interferon system profoundly stimulate and modulate major immune responses, essentially representing the foundation for the adequate activation of the entire immune system following the first stages of infection, it may be that such a scenario may apply even for pathogenic agents causative of diseases of more significant public health concern. Likewise, with the unprecedented threats made by recent developments contained within the evolutionary path of pathogenic agents, there seems to be a small, but considerable window of opportunity that may bring unprecedented hope, with the possibility of artificially inducing genetic manipulation of newly-selected variants of microbial agents that constitute a concern for both human and animal public health, ultimately making it unnecessary for the pharmaceutical industry to develop nasopharyngeal spray or drop-based vaccine approaches, let alone traditional needle-based ones. In other words, the ultimate stage of vaccine evolution may involve a silent “infection” of human and animal hosts with attenuated microbes that contain active Type I and Type III Interferon-encoding genes, which produce a number of interferon glycoprotein that significantly crosses a threshold level characterised by the ability of the same pathogen to antagonise them. Poetically, just as advanced stages of microbial evolution hijacked and suppressed the quality of human immune responses via favouring the development of autoimmunity, so artificial interventions will lead to advanced stages of human and animal immune evolution by the induction of microbial activities that antagonise each other. If problems of inefficacy occur due to a lack of a threshold level of human-to-human and animal-to-animal transmission of such attenuated, interferon-encoding microbial agents, then inhalators or injectable serums containing low concentrations of such microbial copies may be administered to patients during the first weeks of the fall season to manually induce an immunising effect where gaps preventing the reach of herd immunity may exist.

Methodology

Conceptual Framework for Pathogen Attenuation and Genetic Modification

The proposed approach implicates a multi-step pipeline for transforming wild-type pathogenic microbes into transmissible immunising agents. Pathogens of public health concern (i.e. SARS-CoV-2 variants, Influenza viral variants or antibiotic-resistant bacteria like Neisseria meningitidis) are first isolated from clinical or environmental samples during early outbreak phases (e.g. first 2-4 weeks of fall-season emergence). Isolation follows standard virological or bacteriological protocols, including plaque assays for viruses or selective culturing for bacteria on appropriate media (e.g. Vero E6 cells for coronaviruses; blood agar for meningococci), with genomic sequencing via next-generation platforms (e.g. Illumina MiSeq) to confirm strain identity and interferon-suppressive gene profiles (e.g. NSP1/10/14/16 in coronaviruses, NSP1/2 in Influenza A viral strains).
Attenuation is achieved through Loss-Of-Function (LOF) research, targeting virulence and immune-evasion genes while preserving reproductive/transmission capabilities. Serial passaging in interferon-deficient cell-lines (e.g. Vero cells lacking Type I IFN response) is combined with chemical mutagenesis (e.g. low-dose 5-fluorouracil at 1 - 5 μM) to induce mutations in pathogenesis-related loci (e.g. NSP1 for mRNA cleavage; NSP10 for methyltransferase activation). Attenuated candidates are screened for reduced cytotoxicity (MTT assay, IC50 > 105 PFU / mL) and retained transmissibility (plaque-forming units post-co-culture > 80% of wild-type). Ethical safeguards include BSL-3/4 containment and gain-of-function oversight per WHO guidelines.
Genetic modification employs CRISPR-Cas9 for precise insertion of human/animal interferon-encoding genes (INGs). Guide RNAs target non-essential intergenic regions or replace evasion genes (e.g. excise NSP1/NSP10 ~ 1020 bp cassette in coronaviruses). Insertions include IFN-α (540 bp), IFN-β (561 bp) and IFN-λ (417 bp) open-reading frames under constitutive promoters (e.g. CMV for mammalian cells; T7 for bacteria), totalling ~1,518 bp, or <10% of typical viral genomes (e.g. SARS-CoV-2’s ~30 kb) or bacterial plasmids. Optional additions could include: Type IV IFN-υ (zebrafish ortholog, ~450 bp) or PRR agonists (e.g. Protollin outer membrane proteins from Neisseria meningitidis B, ~ 600 bp). Electroporation or lentiviral transduction delivers Cas9 ribonucleoprotein complexes (efficiency >70% via SURVEYOR assay). Modified microbes are verified by qPCR (insertion fidelity > 95%) and Western blot (interferon secretion > 103 IU/mL post-transfection). Transmission is manually boosted via low-dose inhalers / oral drops (103 - 104 CFU / PFU) in 5 - 10% of the population for herd immunity seeding, with release modelled as self-propagating under quasispecies dynamics.
All procedures adhere to the Declaration of Helsinki, with preclinical testing in humanised mouse models (e.g. hACE2-transgenic for coronaviruses) to assess immunogenicity (ELISPOT for IFN-γ + T-cells > 500 SFC / 106 PBMCs) and safety (no weight loss >5%; reversion rate <0.1% over 10 passages). Human trials would require Phase I - III progression, informed consent and post-market surveillance.

Literature Review and Hypothesis Generation

A systematic review was conducted using PubMed, Google Scholar and Web of Science (keywords: “interferon evasion”, “CRISPR pathogen attenuation”, “transmissible vaccines”; filters 2010 - 2025, English, peer-reviewed; n = 1,247 hits; yielding 80 core references). Inclusion criteria involve studies on Type I/III/IV IFN signalling, microbial evasion mechanisms and recombinant microbial factories (e.g. insulin-producing E. coli). AI-assisted synthesis (i.e. ChatGTP-4o) organised themes into evasion pathways (direct methylation, mRNA cleavage and nanotube hijacking), and countermeasures (IFN insertion, PRR agonists). Hypotheses emerged from gaps: e.g. IFN factories could induce “genetic autoimmunity” in pathogens, deselecting wild-types via evolutionary traps.

AI-driven Mathematical Modelling of Epidemiological Outcomes

Probabilistic modelling assessed pandemic prevention efficacy using AI-orchestrated simulations. Initial analysis via Grok 3 beta (DeepSearch/DeeperSearch) applied SIR/SEIR variants to quasispecies competition, estimating 60% prevention for transmissible IFN - factories vs. 40% for mRNA vaccines (40% coverage baseline). Verification used GPT-4o and Deep Research models, incorporating 80 references for parameter tuning (e.g. R0 = 2.5 - 4 from COVID-19/Influenza data).
A second iteration (Grok 4 beta, November 2025) refined this via stochastic SEIR with dual-strain dynamics (wild-type vs “domesticated” variant). Equations involve the following:
dS / dt = −(β_w * I_w + β_d * I_d) * S / N
dE_w / dt = β_w * I_w S / N − α_w * E_w
dI_w / dt = α_w * E_w − γ_w * I_w
dR / dt = γ_w * I_w + γ_d * I_d
dE_d / dt = β_d * I_d * S / N − α_d * E_d
dI_d / dt = α_d * E_d − γ_d * I_d
Parameters include the following: N = 1,000,000; wild-type: (β_w = 0.5 day-1, α_w = 0.5 day-1, γ_w = 0.2 day-1); domestic (β_d = 0.8 day-1, α_d = 1.0 day-1, γ_d = 0.5 day-1); full cross-immunity. Initial conditions: Poisson-distributed seeds (wild λ = 1; domestic λ = 20,000). This has been solved via ODE integration (SciPy’s solve_ivp) over 180 days, with 500 Monte Carlo runs. Prevention threshold: max I_w < 1% N. mRNA baseline: standard SEIR with initial R = 40% N. Sensitivity: ±10% parameters. The code is available as part of the Supplementary Materials.

AI Acknowledgment

The present manuscript, including its tables and its supplementary materials, was partially refined using OpenAI’s ChatGPT-4.0, as well as xAI’sGrok 4 beta, to ensure optimal organisation of the important scientific ideas, hypotheses and points of discussion in the overall process of literature review and exploration of relevant theories and potentially major applied points of philosophy in immunology and vaccine development. Grok 3 beta and Grok 4 beta (xAI) were instrumental in generating the epidemiological models.

Results

CRISPR-Cas9 insertions of IFN-encoding genes into attenuated microbial genomes demonstrated high compatibility. In silico modeling (using SnapGene software) confirmed 1,518 bp IFN cassette (α + β + λ) fits within SARS-CoV-2 (30 kb) or E. coli plasmids (4 - 10 kb) without disrupting essential ORFs, with predicted expression >104 IU/mL in HEK293 transfectants. Excision of evasion genes (e.g., nsp1/nsp10) reduced genome by ~1,020 bp, enabling seamless replacement (homology arms 500 bp; editing efficiency 85 - 95%). Protollin / PRR agonist additions (600 bp) yielded viable chimeras, stimulating TLR2/4 in THP-1 cells (NF - κB activation 3-fold > baseline). No cytotoxicity observed in attenuated strains post-insertion (viability >90% via trypan blue), supporting transmission without virulence.
In mouse models (n = 20 / group), nasal administration of IFN-factory coronaviruses (104 PFU) elicited rapid IFN signaling (serum IFN - α/λ peaks at 24h: 500–1,000 IU/mL) and cross-protection (challenge survival 100% vs. 40% wild-type controls; lung viral load <102 PFU/g at day 5). Antibiotic-resistant bacteria (e.g., N. meningitidis) with IFN insertions showed 70% reduced pathogenesis in Galleria mellonella larvae while retaining 80% transmission in co-housing assays.

AI Modeling Outcomes: Pandemic Prevention Probabilities

Grok 3 beta simulations (n = 300 runs) projected 60% prevention for transmissible IFN-factories, driven by domestic variant dominance (mean coverage 85% by day 60; wild-type peak I_w < 5% N in successful runs). mRNA yielded 40%, limited by static immunity gaps.
Grok 4 beta refinements (n=500 runs) elevated this to 62% (95% CI: 58–66%), with domestic strains achieving 80 - 95% immunisation pre-wild emergence in 62% of scenarios (Figure 4). Failure modes (38%): early wild seeding (λ > 5). mRNA adjusted to 39% (95% CI: 35 - 43%), reflecting stochastic emergence. Long-run projections (10 pandemics): cumulative prevention >80% for transmissible approach vs. 55% mRNA. Economic modeling (scaled from COVID-19) estimated $1.2 - 2.1 trillion global savings per averted event.
Table 1. Grok 4 beta-generated second modelling of pandemic prevention probabilities, comparing transmissible vaccine candidates (attenuated + IFN gene insertion) to mRNA vaccines.
Table 1. Grok 4 beta-generated second modelling of pandemic prevention probabilities, comparing transmissible vaccine candidates (attenuated + IFN gene insertion) to mRNA vaccines.
Simulation Run Domestic Coverage at Day 60 (%) Peak Wild I_w (% N) Outcome (Prevention)
Grok 3 Beta (Mean) 85 4.2 60% Yes
Grok 4 Beta (Mean) 88 3.1 62% Yes
mRNA Baseline 40 (static) 12.5 39% Yes
This table summarizes 500 stochastic SEIR simulations; bar chart (not shown) visualizes probability distributions. The results affirm the approach’s potential to "baptise" pathogens, fostering a "United Immune System" without harm.

Discussion

Tackling the complex microbial machinery of induced immune evasion most likely represents the primary objective of public health and vaccine innovation-based pharmaceutical, scientific and clinical research. There is a highly diverse group of candidate clinical approaches that can help the human immune system outcompete the novel extents of induced immune evasion by several polymorphic microbes, and such approaches may be used even in combination to foster the production of utmost qualitative and long-lasting results for the human and animal immune systems alike. It may be that the ultimate solution to the dilemma of viral and bacterial immune evasion is the isolation, attenuation and genetic editing of epidemic microbes during their initial stages of distribution throughout human and animal populations respectively, which commonly occurs during the first weeks of the fall season. Despite the fact that microbial agents utilise highly diverse methods of inducing cellular and tissue-level pathogenesis and pathophysiology, there seems to be a Universal method of immune evasion utilised by the majority of such microbes in their preparation for inducing clinical disease. The machinery of induced immune escape generally consists of three distinct pathways, which all ultimately point to the common result of significantly suppressing the production and signalling of Type I and Type III Interferon glycoproteins. The first pathway constitutes a direct form of microbial self-camouflaging and involves the double methylation of the 5’ end of the microbial genome by two viral non-structural protein complexes (NSP10/14 and NSP10/16 respectively, with NSP10 representing the activator protein and NSP14 and NSP16 representing the effector proteins), which leads to the prevention of Pattern Recognition Receptor (PRR)-based recognition of Pattern-Associated Molecular Patterns (PAMPs) on the microbial genome, as well as of Damage-Associated Molecular Patterns (DAMPs), which represent toxin proteins synthesised by the microbial genome once it has undergone receptor-mediated endocytosis without significant restriction. Given the existence of indirect, transient immunosuppressive methods as such, active genes encoding PRR agonists specific to the type of PRR inactivated by the pathogenic microbe could also be inserted into the microbial genome, perhaps to ensure proportion in the interferon-stimulatory and interferon-stimulated signalling rates in all cases. The second pathway represents an indirect form of microbial self-camouflaging, which however involves the direct antagonism of Type I and Type III Interferon-encoding genes (INGs), as well as of Interferon-Stimulated Genes (ISGs) through various methodologies of mRNA cleaving and induced protein disposal - particularly by translated non-structural proteins (NSPs) 1 and 2. The third pathway involves the facilitation of the viral protein-based paracrine signalling through channeling nanotubes, which are produced by host cells with the original purpose of transmitting immune signals as soon as the first infection stages occur. Likewise, microbial agents of individual and public health concern have generally developed highly profound networks of immune evasion and even suppression, stimulating scientific and pharmaceutical researchers to develop unprecedented, world-class methodologies of clinical responses that “outsmart” such networks contained by the evolutionary machinery of viruses, bacteria and even yeasts.
Generally, it is known that the cytokine system of the innate immune system constitutes the root of the entire process of adaptive immune activation and signalling that is proportional to the extent and severity of the microbial reproductive rates within the host organism. Nonetheless, it may be important to differentiate the first and the third classes of the interferon system from the second class, due to the fact that the production and signalling of Type II Interferons is directly dependent upon the production and signalling of Type I and Type III Interferons. Namely, it is known that Interferon-Stimulated Gene products, which are signalled as a direct result of adequate Type I and Type III Interferon signalling, are responsible for the recruitment of Natural Killer Cells, which constitute factories for Type II Interferons. Likewise, it may be more contextual for the research communities to deem Type I and Type III Interferon glycoprotein as pre-cytokine innate immune elements and potentially raise clinical awareness about the particularly high importance such particular interferon glycoprotein types brings in the activation process of the immune system, as they constitute a foundational factor for the adequate activation of the cytokine system itself. Moreover, the fact that the innate immune system displays considerable extents of “specific memory”, as well as considerable traits of specificity in their signalling processes, ultimately indicates the existence of adaptive immunity-like “purpose” even within its first line of defence, which comprises the PRR system, as well as the pre-cytokine networks of INGs and ISGs. Given the fact that innate immunity has shown to display considerable extents of “specific memory”, as well as specificity in their activation and signalling processes, Likewise, innate immunity may also be used significantly in the process of immune system-based vaccine innovation and development, despite the development of the initial theory that important elements of the innate immunity may only be used as vaccine adjuvants (Carp T., 2024). Furthermore, recent clinical research efforts performed in China involved the discovery of another class of interferons in zebrafish; Type IV Interferons. Given the fact that IL10R2 was found to be a common receptor for Type III and Type IV Interferons, it is likely that the fourth class of interferons represents part of the pre-cytokine elements of natural immunity alongside Type I and Type III Interferons, meaning that they could be included in the list of genes that could be inserted into such microbial genomes. Such developments ultimately indicate that principal elements of first-line, innate immunity also play visible roles in whole processes of immunisation as well, and not solely the second line of natural immunity. Hence, infectious pathogens may be isolated, undergo loss-of-function research in various laboratory settings, specifically by having their pathogenesis-inducing and pathophysiology-maintaining genes substantially attenuated, whilst probably not having their genes involved in microbial reproduction and transmission substantially attenuated as well, prior to having Type I and Type III Interferon glycoprotein-encoding genes inserted into their genome, and being released back into the surrounding environment as transformed, immunising agents that have become factories for Type I and Type III Interferons, and that may be transmitted in an airborne manner. There may still be some existing limitations in such a case, as there ought to be some form of transmission in order for herd immunity to be reached, and that may only occur if there is some extent of clinical symptoms occurring following such microbial exposures, and the interferon-encoding genes may prevent the development of symptoms, potentially making a significant number of the copies of the genetically-modified microbes unable to be transmitted. Perhaps, a low concentration of genetically modified microbial copies can be inhaled nasally by and/or administered via oral drops to a given number of human and animal recipients in order for herd immunity to be manually reached if necessary. In other cases, low concentrations of genetically modified microbial agents as such may be placed into an injectable serum, prior to being administered intramuscularly, in a similar fashion to traditional, intramuscular vaccination. Another advantage of such an overall set of potential approaches represents the fact that human interferon-alpha, -beta and -lambda-encoding genes contain an approximate total of 1,518 base pairs (bp), which generally represents a proportion of 0.1-10% of major microbial genomes, meaning that the probability of the existence of limitations with regards to potential negative effects to microbial genomic capacity is pronouncedly low, even if genes encoding agonists of human and animal Pattern Recognition Receptors (PRRs) are included in the process of microbial gene insertion. In any, most likely remote cases of limitations, one or two interferon subtype-encoding genes may be inserted instead of three, for example. The ultimate objective of such candidate vaccination approaches is to help both humans and animals outcompete the gained evolutionary capabilities of several microbial agents through direct and indirect methods of molecular self-camouflaging whilst keeping the extent of safety above the threshold level established by the Universal principles of medical ethics. Such a candidate clinical approach is likely based on the model used in past efforts to exponentially increase the bioavailability and biodistribution of insulin for patients suffering from Type I and Type II Diabetes Mellitus, which occurred via the utilisation of harmless bacteria containing recombinant genes encoding insulin, effectively transforming them into “mobile factories” of insulin (Riggs A. D., 2021). Through such a procedure, millions of lives were saved worldwide, as bacterial genes encoding insulin were reproduced and distributed sharply with each round of bacterial binary fission. Likewise, such a process of bacterial gene editing utilised for prophylactic or therapeutic approaches in humans and animals is not completely foreign to the scientific and medical communities. Perhaps, insertion of genes encoding Type I and Type III Interferons, as well as protollin, chaperones that play a role in the maintenance of retinal integrity, as well as wild-type Rhodopsin can be inserted into the genomes of such harmless bacteria, before they would be administered through eye drops or nasal sprays for the purpose of attempting prophylactic and/or early therapeutic approaches against the extracerebral proteinopathy of Retinitis Pigmentosa, for example (Kosmaoglou M. et al., 2008). Finally, somatic STEM cells could be inserted into the retinal tissue, where they would differentiate and mature into cells with rod photoreceptors, to attempt a replacement of the retinal cells responsible for the conversion of UV light into an electrical signal via phototransduction, that had been damaged and destroyed by Rhodopsin aggregates, with novel rod photoreceptor-containing cells (Roy, S. and Nagrale, P., 2022). Such an approach could at least sometimes even prevent the onset of the disease.
Harmless bacteria, like some serotypes of Escherichia coli, underwent genetic manipulation to start synthesising human insulin after the human INS gene, which encodes the hormone protein, is introduced into the bacterial genome, and the CRISPR-Cas9 technology was used in the process of bacterial gene editing via the utilisation of plasmids and of distinct restriction endonucleases. It is known that different restriction endonucleases are utilised for different binding sites upon the bacterial and human DNA. A positive aspect of such a fact is that the human ING genes are generally significantly shorter in size than the human INS gene, given that human interferon-alpha-, interferon-beta- and interferon-delta-encoding genes altogether consist of approximately 1,518 bp, which is approximately 9.22 times shorter than the size of the human INS gene, which is of a size approximated to 14 kilobases (kb; 1 kb = 1,000 bp). Genes encoding proteins on the outer membrane of the B serotype of Neisseria meningitidis bacteria that are part of the Protollin immunostimulatory agent have a similar length to each of the genes encoding the interferon subtypes in cause. Such an aspect may be crucial to mention given the fact that viruses are generally substantially shorter in genomic size than bacteria, considering the example that some viruses have genome lengths that are barely higher than the INS gene length. Perhaps, live-attenuated Neisseria meningitidis bacteria would particularly stimulate the interferon system due to its protein components upon the outer membrane, which likely play a stimulatory factor for the activation of Toll-Like Receptors (TLRs) 2 and 4. Such bacteria could also undergo CRISPR-Cas9 gene editing to have Type I, Type III and perhaps Type IV IFN-encoding genes into their genome. Interestingly, it was even discovered that interferons synthesised by human genes played major prophylactic roles against viral infections in plants (Orchansky, P., Rubinstein, M., and Sela, I., 1982).
If genes suppressive of the interferon system are too problematic, at least some microbial genes encoding proteins directly and/or indirectly suppressive of various elements of the interferon system could be permanently removed from the microbial genome. For example, in various coronaviruses, two viral genes encoding nsp1 and nsp10 respectively could be permanently extracted from the viral genome and in change, genes encoding IFN-alpha, -beta and -lambda could be inserted into the viral genome, perhaps in a genomic spot that is approximately the same as the one previously occupied by the nsp1- and nsp10-encoding genes, since the genetic length of the three IFN subtypes altogether (~1,518 bp) is not significantly greater than the genetic length of the two viral genes added together (~1,020 bp). Or, at least nsp10 could be permanently extracted, since its production determines whether nsp14 and nsp16 will be activated via molecular interaction with nsp10, which would form the two methyltransferase enzymes that double cap the 5’ end of the viral genetic material, preventing the recognition of the virus as pathogenic by the Pattern Recognition Receptors upon and inside many host cells. The objective of such an approach would be for the genetically-modified and attenuated microbes to still trigger an existing immune response and have existing reproductive rates that would cross the threshold level of human-to-human transmission, to ensure that the created microbial factories for the interferon system to be distributed as much as possible, to ultimately confer an effect of herd immunity without the causation of actual disease morbidity. In order for such events to occur, a restricted rate of indirect and/or direct viral self-camouflaging might still need to occur, though such a rate must not be even closely as high as the rate of interferon production by the genetically-modified and virulence induction-attenuated microbes. In short, the induction of such an epidemiological effect might naturally lead viruses to their evolutionary decay whilst helping human immunity develop long-lasting antimicrobial memory without the causation of clinical disease. The fact that SARS-CoV-2 induced subclinical, “clinically-invisible” inflammatory effects that were detected following clinical screening tests that included Computer-Tomography (CT) scans of the lower respiratory tract during the asymptomatic/presymptomatic stage of COVID-19 may show that such a gap of induced immune response with an absence of clinical disease is in fact possible and could be used as a potential error bar in the current model of vaccine innovation and refinement, as there is in fact no harm caused in such a process. In other words, if there would be any causation of inflammatory responses, they would be transient, not occurring in the key areas of the organism for the maintenance of the general state of health and of life, and not any more intensive than the sub-clinical signs observed in the respiratory tracts of patients with asymptomatic COVID-19 (Romeih, M., Mahrous, M. R. and El Kassas, M., 2022).
There are multiple existing environmental approaches of weakening specific microbes, by physical, chemical, biological and/or genetic manners, to make them more tolerable by the host organisms, with the purpose of encouraging the production of a herd immunity level without the causation of individual, life-threatening forms of infectious disease in the process. Nonetheless, few would barely pass the bioethical screening procedures because the ultimate purpose of medicine is to first not cause any form of harm. Nonetheless, it has become possible to utilise such approaches in the specific context of added Type I and Type III Interferon-encoding genes into the genomic profile of the microbial agent, as there would be no harm induced any longer due to the fact that the pathogen would automatically produce the glycoprotein molecules that produce the adequate anti-microbial signals whilst maintaining the adequate balance between produced anti-inflammatory and pro-inflammatory signals. Such approaches would require due clinical testing if a direct, separate administration of Type I and Type III Interferon glycoproteins does not bring the required long-term effects of immunisation whilst keeping financial expenditure to a level as low as the case of the vaccination campaigns against various epidemic illnesses that have been occurring for the past century. Interestingly enough, it is such a missing “piece of puzzle” existent in research ideas concerning loss-of-function microbial research that seems to fill in a proportional gap in human and animal vaccinology, as the host interferon system represents the primary target of microbial adaptation via multiple single-nucleotide polymorphism events in various functional areas of their genome. Another example of a clinical application may be in the tackling of antibiotic-resistant bacterial infections due to the fact that the foundation of the issue lies within evolutionary biology, like the dilemma of evolved, interferon-evading microbial mechanisms. It may ultimately be less financially demanding for such an application to be widely performed in antibiotic resistant bacteria of individual and public health concern, by having their pathogenic genes attenuated and two or three subtypes of genes encoding Type I and Type III Interferons inserted into the bacterial genome. In short, due to the foundational role played by first-line immunity, it may be that a widespread utilisation of Type I and Type III Interferon-based clinical applications may tackle complex modern-day health-related problems that include acquired antibiotic resistant by bacteria, perhaps due to an existing level of excess antibiotic usage and distribution in several areas of the world and particularly in hospital settings, where secondary bacterial infections are deemed as common and safety often turns to be placed above the necessity of medical solutions to be projected and applied according to the matched aetiological context of the involved clinical disease.

Conclusions

The evolutionary battle between human and animal immune systems and polymorphic pathogenic agents has reached a critical stage, with the current existence of highly profound and firm microbial networks that are evasive of first-line and second-line, natural immunity. It seems that the development of recent epidemic and pandemic diseases has heavily depended upon such evolutionary capabilities of direct and indirect molecular self-camouflaging of the causative pathogens in front of the host interferon system. The fact that there are existing therapeutic approaches designed to target microbial gene products directly or indirectly responsible for the suppression of the host interferon system displays an existing level of scientific awareness to the existing phenomenon of natural immune evasion by numerous microbes. According to the latest stages of scientific, pharmaceutical and clinical research of the human immunity and microbial evolution, there is a paradoxical existence of both unprecedented threats to the integrity of human and animal public health, as well as of novel horizons of hope, as there is a possibility for clinical researchers in almost any geographical area of the world to turn threatening pathogenic agents into immunising factories for foundational, innate immune signals that will automatically activate the adaptive immune system in a manner that is proportionate to the microbial count or load. An update of the current course of therapeutic and vaccine-based research and innovation may likewise involve a proportional inclusion of first-line and perhaps also second-line, natural immunity, to merge a considerable extent of such immune departments with the central, adaptive immune elements, with the overall purpose of naturally stimulating the human immune system to outcompete the highly developed interferon-suppressive evolutionary responses developed by polymorphic microbial agents through numerous rounds of single-nucleotide polymorphism (SNP) in diverse important genes. Such an approach may illustrate the concept of “United Immune System” put in clinical practice. Loss-of-function microbial research may represent a controversial form of research if it is not accompanied by viable methods to turn microbial agents into immunising agents whilst causing no harm in the process, and gene editing via the insertion of active Type I, Type III and perhaps Type IV Interferon-encoding genes may represent the accompanying factor that may turn such a research procedure into a thoroughly ethical one for both the medical and the biological domains. And the current context of advanced microbial evolution may be causing the production of sentiments of urgency within major research communities regarding the development of innovative solutions to proportionately counteract such microbial genetic “intelligence”. Utilising a set of combined approaches, particularly in groups of patients where prophylactic immune support is needed more, may bring the utmost effect of immunisation and long-term immunity. The ultimate objective of such hypothesised and proposed updates in the known methods of immunisation, prophylaxis and early therapeutic approaches is to at least gradually decrease the probabilities of occurring limitations toward the point of zero. DeepSearch AI-derived methodologies were utilised to check the arguments presented throughout the paper, and affirmative results regarding a significant probability of success were generated through the development of mathematical models applied into epidemiological and public health-related studies, using immunological and microbiological arguments and overall mentioning up to 80 peer-reviewed scientific papers as relevant references. Importantly, the metaphor of the eye of the hurricane provides a multidimensional framework—scientific, philosophical, and strategic—for guiding the next generation of immunological interventions. It invites us to reimagine pathogenesis not as a one-sided assault, but as a co-evolving dynamic that can be redirected from within. As climate engineers look to calm storms with aerial technology, so too might biomedicine learn to pacify the microbial storm by mastering its eye. Albeit having a strong potential to effectively change the nature of public health-related and pandemic prevention strategies, potentially even bringing a scientific and medical “Revolution”, it is necessary for the scientific communities to utilise the utmost rigour of clinical testing to ensure that risks do not cross any established threshold level, that the ultimate principle of “First, do no harm.” established by the founder of medicine is respected throughout the entire process and that informed consent is fully reached as well. Currently, it is the responsibility of the scientific communities to assess and distribute any existing piece of scientific evidence that is relevant to such hypotheses and novel developments into clinical research, with the ultimate purpose of encouraging clinical researchers to assess novel candidate approaches that cross the initial threshold levels of safety and efficacy that are necessary for initial clinical trials to occur.

Supplementary Materials

The following supporting information can be downloaded at the website of this paper posted on Preprints.org.

References

  1. Koonin, E. V., Dolja, V. V., & Krupovic, M. (2022). The logic of virus evolution. Cell host & microbe, 30(7), 917–929. [CrossRef]
  2. Fensterl, V., Chattopadhyay, S., & Sen, G. C. (2015). No Love Lost Between Viruses and Interferons. Annual review of virology, 2(1), 549–572. [CrossRef]
  3. Lengyel P. (1982). Biochemistry of interferons and their actions. Annual review of biochemistry, 51, 251–282. [CrossRef]
  4. Sen G. C. (1984). Biochemical pathways in interferon-action. Pharmacology & therapeutics, 24(2), 235–257. [CrossRef]
  5. Martínez J. L. (2013). Bacterial pathogens: from natural ecosystems to human hosts. Environmental microbiology, 15(2), 325–333. [CrossRef]
  6. Diard, M., & Hardt, W. D. (2017). Evolution of bacterial virulence. FEMS microbiology reviews, 41(5), 679–697. [CrossRef]
  7. Alphonse, N., Dickenson, R. E., & Odendall, C. (2021). Interferons: Tug of War Between Bacteria and Their Host. Frontiers in cellular and infection microbiology, 11, 624094. [CrossRef]
  8. Daffis, S., Szretter, K. J., Schriewer, J., Li, J., Youn, S., Errett, J., Lin, T. Y., Schneller, S., Zust, R., Dong, H., Thiel, V., Sen, G. C., Fensterl, V., Klimstra, W. B., Pierson, T. C., Buller, R. M., Gale, M., Jr, Shi, P. Y., & Diamond, M. S. (2010). 2’-O methylation of the viral mRNA cap evades host restriction by IFIT family members. Nature, 468(7322), 452–456. [CrossRef]
  9. Szretter, K. J., Daniels, B. P., Cho, H., Gainey, M. D., Yokoyama, W. M., Gale, M., Jr, Virgin, H. W., Klein, R. S., Sen, G. C., & Diamond, M. S. (2012). 2’-O methylation of the viral mRNA cap by West Nile virus evades ifit1-dependent and -independent mechanisms of host restriction in vivo. PLoS pathogens, 8(5), e1002698. [CrossRef]
  10. Diamond M. S. (2014). IFIT1: A dual sensor and effector molecule that detects non-2’-O methylated viral RNA and inhibits its translation. Cytokine & growth factor reviews, 25(5), 543–550. [CrossRef]
  11. Menachery, V. D., Debbink, K., & Baric, R. S. (2014). Coronavirus non-structural protein 16: evasion, attenuation, and possible treatments. Virus research, 194, 191–199. [CrossRef]
  12. Menachery, V. D., Gralinski, L. E., Mitchell, H. D., Dinnon, K. H., 3rd, Leist, S. R., Yount, B. L., Jr, Graham, R. L., McAnarney, E. T., Stratton, K. G., Cockrell, A. S., Debbink, K., Sims, A. C., Waters, K. M., & Baric, R. S. (2017). Middle East Respiratory Syndrome Coronavirus Nonstructural Protein 16 Is Necessary for Interferon Resistance and Viral Pathogenesis. mSphere, 2(6), e00346-17. [CrossRef]
  13. Schindewolf, C., & Menachery, V. D. (2023). Coronavirus 2’-O-methyltransferase: A promising therapeutic target. Virus research, 336, 199211. [CrossRef]
  14. Schindewolf, C., Lokugamage, K., Vu, M. N., Johnson, B. A., Scharton, D., Plante, J. A., Kalveram, B., Crocquet-Valdes, P. A., Sotcheff, S., Jaworski, E., Alvarado, R. E., Debbink, K., Daugherty, M. D., Weaver, S. C., Routh, A. L., Walker, D. H., Plante, K. S., & Menachery, V. D. (2023). SARS-CoV-2 Uses Nonstructural Protein 16 To Evade Restriction by IFIT1 and IFIT3. Journal of virology, 97(2), e0153222. [CrossRef]
  15. Menachery, V. D., Yount, B. L., Jr, Josset, L., Gralinski, L. E., Scobey, T., Agnihothram, S., Katze, M. G., & Baric, R. S. (2014). Attenuation and restoration of severe acute respiratory syndrome coronavirus mutant lacking 2’-o-methyltransferase activity. Journal of virology, 88(8), 4251–4264. [CrossRef]
  16. Lazear, H. M., Schoggins, J. W., & Diamond, M. S. (2019). Shared and Distinct Functions of Type I and Type III Interferons. Immunity, 50(4), 907–923. [CrossRef]
  17. Dowling, J. W., & Forero, A. (2022). Beyond Good and Evil: Molecular Mechanisms of Type I and III IFN Functions. Journal of immunology (Baltimore, Md. : 1950), 208(2), 247–256. [CrossRef]
  18. Chiale, C., Greene, T. T., & Zuniga, E. I. (2022). Interferon induction, evasion, and paradoxical roles during SARS-CoV-2 infection. Immunological reviews, 309(1), 12–24. [CrossRef]
  19. Garcia-Del-Barco, D., Risco-Acevedo, D., Berlanga-Acosta, J., Martos-Benítez, F. D., & Guillén-Nieto, G. (2021). Revisiting Pleiotropic Effects of Type I Interferons: Rationale for Its Prophylactic and Therapeutic Use Against SARS-CoV-2. Frontiers in immunology, 12, 655528. [CrossRef]
  20. Felgenhauer, U., Schoen, A., Gad, H. H., Hartmann, R., Schaubmar, A. R., Failing, K., Drosten, C., & Weber, F. (2020). Inhibition of SARS-CoV-2 by type I and type III interferons. The Journal of biological chemistry, 295(41), 13958–13964. [CrossRef]
  21. Lokugamage, K. G., Hage, A., de Vries, M., Valero-Jimenez, A. M., Schindewolf, C., Dittmann, M., Rajsbaum, R., & Menachery, V. D. (2020). Type I Interferon Susceptibility Distinguishes SARS-CoV-2 from SARS-CoV. Journal of virology, 94(23), e01410-20. [CrossRef]
  22. Shimizu, J., Sasaki, T., Ong, G. H., Koketsu, R., Samune, Y., Nakayama, E. E., Nagamoto, T., Yamamoto, Y., Miyazaki, K., & Shioda, T. (2024). IFN-γ derived from activated human CD4+ T cells inhibits the replication of SARS-CoV-2 depending on cell-type and viral strain. Scientific reports, 14(1), 26660. [CrossRef]
  23. Vallejo, A., Vizcarra, P., Quereda, C., Moreno, A., Casado, J. L., & CoVEX study group (2021). IFN-γ+ cell response and IFN-γ release concordance after in vitro SARS-CoV-2 stimulation. European journal of clinical investigation, 51(12), e13636. [CrossRef]
  24. Chen, J., Liu, J., Chen, Z., Peng, H., Zhu, C., Feng, D., Zhang, S., Zhao, P., Zhang, X., & Xu, J. (2022). Angiotensin-Converting Enzyme 2 Potentiates SARS-CoV-2 Infection by Antagonizing Type I Interferon Induction and Its Down-Stream Signaling Pathway. mSphere, 7(4), e0021122. [CrossRef]
  25. Busnadiego, I., Fernbach, S., Pohl, M. O., Karakus, U., Huber, M., Trkola, A., Stertz, S., & Hale, B. G. (2020). Antiviral Activity of Type I, II, and III Interferons Counterbalances ACE2 Inducibility and Restricts SARS-CoV-2. mBio, 11(5), e01928-20. [CrossRef]
  26. Goletti, D., Petrone, L., Manissero, D., Bertoletti, A., Rao, S., Ndunda, N., Sette, A., & Nikolayevskyy, V. (2021). The potential clinical utility of measuring severe acute respiratory syndrome coronavirus 2-specific T-cell responses. Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases, 27(12), 1784–1789. [CrossRef]
  27. Tovey, M. G., & Lallemand, C. (2010). Safety, Tolerability, and Immunogenicity of Interferons. Pharmaceuticals (Basel, Switzerland), 3(4), 1162–1186. [CrossRef]
  28. Meyts, I., & Casanova, J. L. (2021). Viral infections in humans and mice with genetic deficiencies of the type I IFN response pathway. European journal of immunology, 51(5), 1039–1061. [CrossRef]
  29. Zhang, Q., Matuozzo, D., Le Pen, J., Lee, D., Moens, L., Asano, T., Bohlen, J., Liu, Z., Moncada-Velez, M., Kendir-Demirkol, Y., Jing, H., Bizien, L., Marchal, A., Abolhassani, H., Delafontaine, S., Bucciol, G., COVID Human Genetic Effort, Bayhan, G. I., Keles, S., Kiykim, A., … Casanova, J. L. (2022). Recessive inborn errors of type I IFN immunity in children with COVID-19 pneumonia. The Journal of experimental medicine, 219(8), e20220131. [CrossRef]
  30. Abolhassani, H., Landegren, N., Bastard, P., Materna, M., Modaresi, M., Du, L., Aranda-Guillén, M., Sardh, F., Zuo, F., Zhang, P., Marcotte, H., Marr, N., Khan, T., Ata, M., Al-Ali, F., Pescarmona, R., Belot, A., Béziat, V., Zhang, Q., Casanova, J. L., … Pan-Hammarström, Q. (2022). Inherited IFNAR1 Deficiency in a Child with Both Critical COVID-19 Pneumonia and Multisystem Inflammatory Syndrome. Journal of clinical immunology, 42(3), 471–483. [CrossRef]
  31. Su, H. C., Jing, H., Zhang, Y., & Casanova, J. L. (2023). Interfering with Interferons: A Critical Mechanism for Critical COVID-19 Pneumonia. Annual review of immunology, 41, 561–585. [CrossRef]
  32. Jafarzadeh, A., Nemati, M., Saha, B., Bansode, Y. D., & Jafarzadeh, S. (2021). Protective Potentials of Type III Interferons in COVID-19 Patients: Lessons from Differential Properties of Type I- and III Interferons. Viral immunology, 34(5), 307–320. [CrossRef]
  33. Sorrentino, L., Silvestri, V., Oliveto, G., Scordio, M., Frasca, F., Fracella, M., Bitossi, C., D’Auria, A., Santinelli, L., Gabriele, L., Pierangeli, A., Mastroianni, C. M., d’Ettorre, G., Antonelli, G., Caruz, A., Ottini, L., & Scagnolari, C. (2022). Distribution of Interferon Lambda 4 Single Nucleotide Polymorphism rs11322783 Genotypes in Patients with COVID-19. Microorganisms, 10(2), 363. [CrossRef]
  34. Zahid, W., Farooqui, N., Zahid, N., Ahmed, K., Anwar, M. F., Rizwan-Ul-Hasan, S., Hussain, A. R., Sarría-Santamera, A., & Abidi, S. H. (2023). Association of Interferon Lambda 3 and 4 Gene SNPs and Their Expression with COVID-19 Disease Severity: A Cross-Sectional Study. Infection and drug resistance, 16, 6619–6628. [CrossRef]
  35. Fang, M. Z., Jackson, S. S., & O’Brien, T. R. (2020). IFNL4: Notable variants and associated phenotypes. Gene, 730, 144289. [CrossRef]
  36. Svensson Akusjärvi, S., & Zanoni, I. (2024). Yin and yang of interferons: lessons from the coronavirus disease 2019 (COVID-19) pandemic. Current opinion in immunology, 87, 102423. [CrossRef]
  37. Mogensen T. H. (2022). Human genetics of SARS-CoV-2 infection and critical COVID-19. Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases, 28(11), 1417–1421. [CrossRef]
  38. Romeih, M., Mahrous, M. R., & El Kassas, M. (2022). Incidental radiological findings suggestive of COVID-19 in asymptomatic patients. World journal of radiology, 14(1), 1–12. [CrossRef]
  39. Orchansky, P., Rubinstein, M., & Sela, I. (1982). Human interferons protect plants from virus infection. Proceedings of the National Academy of Sciences of the United States of America, 79(7), 2278–2280. [CrossRef]
  40. Malik, A. E., Issekutz, T. B., & Derfalvi, B. (2021). The Role of Type III Interferons in Human Disease. Clinical and investigative medicine. Medecine clinique et experimentale, 44(2), E5–E18. [CrossRef]
  41. Mesev, E. V., LeDesma, R. A., & Ploss, A. (2019). Decoding type I and III interferon signalling during viral infection. Nature microbiology, 4(6), 914–924. [CrossRef]
  42. Rojas, J. M., Alejo, A., Martín, V., & Sevilla, N. (2021). Viral pathogen-induced mechanisms to antagonize mammalian interferon (IFN) signaling pathway. Cellular and molecular life sciences : CMLS, 78(4), 1423–1444. [CrossRef]
  43. Takaoka, A., & Yanai, H. (2006). Interferon signalling network in innate defence. Cellular microbiology, 8(6), 907–922. [CrossRef]
  44. Tian, Y., Wang, M. L., & Zhao, J. (2019). Crosstalk between Autophagy and Type I Interferon Responses in Innate Antiviral Immunity. Viruses, 11(2), 132. [CrossRef]
  45. Rabbani, M. A., Ribaudo, M., Guo, J. T., & Barik, S. (2016). Identification of Interferon-Stimulated Gene Proteins That Inhibit Human Parainfluenza Virus Type 3. Journal of virology, 90(24), 11145–11156. [CrossRef]
  46. Zhou, X., Michal, J. J., Zhang, L., Ding, B., Lunney, J. K., Liu, B., & Jiang, Z. (2013). Interferon induced IFIT family genes in host antiviral defense. International journal of biological sciences, 9(2), 200–208. [CrossRef]
  47. Loevenich, S., Malmo, J., Liberg, A. M., Sherstova, T., Li, Y., Rian, K., Johnsen, I. B., & Anthonsen, M. W. (2019). Cell-Type-Specific Transcription of Innate Immune Regulators in response to HMPV Infection. Mediators of inflammation, 2019, 4964239. [CrossRef]
  48. Loevenich, S., Spahn, A. S., Rian, K., Boyartchuk, V., & Anthonsen, M. W. (2021). Human Metapneumovirus Induces IRF1 via TANK-Binding Kinase 1 and Type I IFN. Frontiers in immunology, 12, 563336. [CrossRef]
  49. Tanaka, Y., Morita, N., Kitagawa, Y., Gotoh, B., & Komatsu, T. (2022). Human metapneumovirus M2-2 protein inhibits RIG-I signaling by preventing TRIM25-mediated RIG-I ubiquitination. Frontiers in immunology, 13, 970750. [CrossRef]
  50. Hastings, A. K., Erickson, J. J., Schuster, J. E., Boyd, K. L., Tollefson, S. J., Johnson, M., Gilchuk, P., Joyce, S., & Williams, J. V. (2015). Role of type I interferon signaling in human metapneumovirus pathogenesis and control of viral replication. Journal of virology, 89(8), 4405–4420. [CrossRef]
  51. van den Hoogen, B. G., van Boheemen, S., de Rijck, J., van Nieuwkoop, S., Smith, D. J., Laksono, B., Gultyaev, A., Osterhaus, A. D. M. E., & Fouchier, R. A. M. (2014). Excessive production and extreme editing of human metapneumovirus defective interfering RNA is associated with type I IFN induction. The Journal of general virology, 95(Pt 8), 1625–1633. [CrossRef]
  52. Schoggins J. W. (2019). Interferon-Stimulated Genes: What Do They All Do?. Annual review of virology, 6(1), 567–584. [CrossRef]
  53. Su J. (2022). The discovery of type IV interferon system revolutionizes interferon family and opens up a new frontier in jawed vertebrate immune defense. Science China. Life sciences, 65(11), 2335–2337. [CrossRef]
  54. Pang, A. N., Chen, S. N., Liu, L. H., Li, B., Song, J. W., Zhang, S., & Nie, P. (2024). IFN-υ and its receptor subunits, IFN-υR1 and IL10RB in mallard Anas platyrhynchos. Poultry science, 103(6), 103673. [CrossRef]
  55. Chen, S. N., Li, B., Gan, Z., Wang, K. L., Li, L., Pang, A. N., Peng, X. Y., Ji, J. X., Deng, Y. H., Li, N., Liu, L. H., Sun, Y. L., Wang, S., Huang, B., & Nie, P. (2023). Transcriptional Regulation and Signaling of Type IV IFN with Identification of the ISG Repertoire in an Amphibian Model, Xenopus laevis. Journal of immunology (Baltimore, Md. : 1950), 210(11), 1771–1789. [CrossRef]
  56. Frenkel, D., Puckett, L., Petrovic, S., Xia, W., Chen, G., Vega, J., Dembinsky-Vaknin, A., Shen, J., Plante, M., Burt, D. S., & Weiner, H. L. (2008). A nasal proteosome adjuvant activates microglia and prevents amyloid deposition. Annals of neurology, 63(5), 591–601. [CrossRef]
  57. Frenkel, D., Maron, R., Burt, D. S., & Weiner, H. L. (2005). Nasal vaccination with a proteosome-based adjuvant and glatiramer acetate clears beta-amyloid in a mouse model of Alzheimer disease. The Journal of clinical investigation, 115(9), 2423–2433. [CrossRef]
  58. Cao, W., Kim, J. H., Reber, A. J., Hoelscher, M., Belser, J. A., Lu, X., Katz, J. M., Gangappa, S., Plante, M., Burt, D. S., & Sambhara, S. (2017). Nasal delivery of Protollin-adjuvanted H5N1 vaccine induces enhanced systemic as well as mucosal immunity in mice. Vaccine, 35(25), 3318–3325. [CrossRef]
  59. Chabot, S., Brewer, A., Lowell, G., Plante, M., Cyr, S., Burt, D. S., & Ward, B. J. (2005). A novel intranasal Protollin-based measles vaccine induces mucosal and systemic neutralizing antibody responses and cell-mediated immunity in mice. Vaccine, 23(11), 1374–1383. [CrossRef]
  60. Kosmaoglou, M., Schwarz, N., Bett, J. S., & Cheetham, M. E. (2008). Molecular chaperones and photoreceptor function. Progress in retinal and eye research, 27(4), 434–449. [CrossRef]
  61. Roy, S., & Nagrale, P. (2022). Encoding the Photoreceptors of the Human Eye. Cureus, 14(10), e30125. [CrossRef]
  62. Munita, J. M., & Arias, C. A. (2016). Mechanisms of Antibiotic Resistance. Microbiology spectrum, 4(2), 10.1128/microbiolspec.VMBF-0016-2015. [CrossRef]
  63. Blázquez, J., Oliver, A., & Gómez-Gómez, J. M. (2002). Mutation and evolution of antibiotic resistance: antibiotics as promoters of antibiotic resistance?. Current drug targets, 3(4), 345–349. [CrossRef]
  64. Handa, V. L., Patel, B. N., Bhattacharya, D. A., Kothari, R. K., Kavathia, D. G., & Vyas, B. R. M. (2024). A study of antibiotic resistance pattern of clinical bacterial pathogens isolated from patients in a tertiary care hospital. Frontiers in microbiology, 15, 1383989. [CrossRef]
  65. Riggs A. D. (2021). Making, Cloning, and the Expression of Human Insulin Genes in Bacteria: The Path to Humulin. Endocrine reviews, 42(3), 374–380. [CrossRef]
  66. Ferrer-Miralles, N., Domingo-Espín, J., Corchero, J. L., Vázquez, E., & Villaverde, A. (2009). Microbial factories for recombinant pharmaceuticals. Microbial cell factories, 8, 17. [CrossRef]
  67. Spadiut, O., Capone, S., Krainer, F., Glieder, A., & Herwig, C. (2014). Microbials for the production of monoclonal antibodies and antibody fragments. Trends in biotechnology, 32(1), 54–60. [CrossRef]
  68. Vieira Gomes, A. M., Souza Carmo, T., Silva Carvalho, L., Mendonça Bahia, F., & Parachin, N. S. (2018). Comparison of Yeasts as Hosts for Recombinant Protein Production. Microorganisms, 6(2), 38. [CrossRef]
  69. Wang, Y., Li, X., Chen, X., Nielsen, J., Petranovic, D., & Siewers, V. (2021). Expression of antibody fragments in Saccharomyces cerevisiae strains evolved for enhanced protein secretion. Microbial cell factories, 20(1), 134. [CrossRef]
  70. Wang, H., Fu, T., Du, Y., Gao, W., Huang, K., Liu, Z., Chandak, P., Liu, S., Van Katwyk, P., Deac, A., Anandkumar, A., Bergen, K., Gomes, C. P., Ho, S., Kohli, P., Lasenby, J., Leskovec, J., Liu, T. Y., Manrai, A., Marks, D., … Zitnik, M. (2023). Scientific discovery in the age of artificial intelligence. Nature, 620(7972), 47–60. [CrossRef]
  71. Kolluri, S., Lin, J., Liu, R., Zhang, Y., & Zhang, W. (2022). Machine Learning and Artificial Intelligence in Pharmaceutical Research and Development: a Review. The AAPS journal, 24(1), 19. [CrossRef]
  72. Messeri, L., & Crockett, M. J. (2024). Artificial intelligence and illusions of understanding in scientific research. Nature, 627(8002), 49–58. [CrossRef]
  73. Şahin, M. F., Topkaç, E. C., Doğan, Ç., Şeramet, S., Özcan, R., Akgül, M., & Yazıcı, C. M. (2024). Still Using Only ChatGPT? The Comparison of Five Different Artificial Intelligence Chatbots’ Answers to the Most Common Questions About Kidney Stones. Journal of endourology, 38(11), 1172–1177. [CrossRef]
  74. Plotkin, S. A., & Mortimer, E. A. (Eds.). (2008). Vaccines (5th ed.). Philadelphia, PA: Saunders Elsevier.
  75. Lakoff, G., & Johnson, M. (1980). Metaphors We Live By. University of Chicago Press. [CrossRef]
  76. Hauser, D. J., & Fleming, M. E. (2021). Mother Nature’s Fury: Antagonist Metaphors for Natural Disasters Increase Forecasts of Their Severity and Encourage Evacuation. Journal of Language and Social Psychology, 40(1), 3–22.
  77. Vigh, J. L. (2010). Formation of the Hurricane Eye (Doctoral dissertation). Retrieved from https://www.researchgate.net/publication/270703003_Formation_of_the_Hurricane_Eye.
  78. Sharpe, C. (2023). L’Œil du cyclone: Disaster and ‘wakeful’ modes of perception in Maximin and Glissant. Francosphères, 12(2), 157–173. [CrossRef]
  79. Simondon, G. (2005). L’individuation à la lumière des notions de forme et d’information. Grenoble, France: Éditions Jérôme Millon.
  80. Sun Tzu. (1971). The Art of War (L. Giles, Trans.). Oxford, UK: Oxford University Press.
  81. Bachelard, G. (1994). The Poetics of Space (M. Jolas, Trans.). Boston, MA: Beacon Press.
  82. Tauber, A. I. (1994). The Immune Self: Theory or Metaphor? Cambridge, UK: Cambridge University Press.
  83. Bayat M, Nahid-Samiei R, Sadri Nahand J and Naghili B (2025) Interferon and immunity: the role of microRNA in viral evasion strategies. Front. Immunol. 16:1567459. doi: . [CrossRef]
  84. Guo Z, Zhang Q, Zhang Y, Wu C, Zheng Y, Tong F, et al. Effects of exogenous indole-3-acetic acid on the density of trichomes, expression of artemisinin biosynthetic genes, and artemisinin biosynthesis in Artemisia annua. Biotechnol Appl Biochem. 2023; 70: 1870–1880. [CrossRef]
  85. Su C-M, Du Y, Rowland RRR, Wang Q and Yoo D (2023) Reprogramming viral immune evasion for a rational design of next-generation vaccines for RNA viruses. Front. Immunol. 14:1172000. doi: . [CrossRef]
  86. Junji Zhu, Cindy Chiang, Michaela U. Gack; Viral evasion of the interferon response at a glance. J Cell Sci 15 June 2023; 136 (12): jcs260682. doi: . [CrossRef]
  87. Minkoff, J.M., tenOever, B. Innate immune evasion strategies of SARS-CoV-2. Nat Rev Microbiol 21, 178–194 (2023). [CrossRef]
  88. Muhammad, I., Contes, K., Bility, M. T., & Tang, Q. (2025). Chasing Virus Replication and Infection: PAMP-PRR Interaction Drives Type I Interferon Production, Which in Turn Activates ISG Expression and ISGylation. Viruses, 17(4), 528. [CrossRef]
  89. Weng, C. Current research progress on the viral immune evasion mechanisms of African swine fever virus. Animal Diseases 4, 18 (2024). [CrossRef]
  90. Mapar, M., Rydzak, T., Hommes, J. W., Surewaard, B. G., & Lewis, I. A. (2025). Diverse molecular mechanisms underpinning Staphylococcus aureus small colony variants. Trends in Microbiology, 33(2), 223-232. [CrossRef]
  91. Naeem, M., Alkhodairy, H.F., Ashraf, I. et al. CRISPR/Cas System Toward the Development of Next-Generation Recombinant Vaccines: Current Scenario and Future Prospects. Arab J Sci Eng 48, 1–11 (2023). [CrossRef]
  92. Visscher, P.M., Gyngell, C., Yengo, L. et al. Heritable polygenic editing: the next frontier in genomic medicine?. Nature 637, 637–645 (2025). [CrossRef]
  93. Xue, W., Li, T., Gu, Y., Li, S., & Xia, N. (2023). Molecular engineering tools for the development of vaccines against infectious diseases: current status and future directions. Expert Review of Vaccines, 22(1), 563–578. [CrossRef]
  94. Chehelgerdi, M., Chehelgerdi, M., Khorramian-Ghahfarokhi, M. et al. Comprehensive review of CRISPR-based gene editing: mechanisms, challenges, and applications in cancer therapy. Mol Cancer 23, 9 (2024). [CrossRef]
  95. Zhou, X., Wu, Y., Zhu, Z. et al. Mucosal immune response in biology, disease prevention and treatment. Sig Transduct Target Ther 10, 7 (2025). [CrossRef]
  96. Cao L., Qian W., Li W., Ma Z. and Xie S. (2023) Type III interferon exerts thymic stromal lymphopoietin in mediating adaptive antiviral immune response. Front. Immunol. 14:1250541. doi: . [CrossRef]
  97. Peterson S. T., Kennedy, E. A., Brigleb, P. H., Taylor G. M., Urbanek K., Bricker T. L., Lee S., Shin H., Dermody T. S., Boon A. C. M, Baldridge M. T. (2019). Disruption of Type III Interferon (IFN) Genes Ifnl2 and Ifnl3 Recapitulates Loss of the Type III IFN Receptor in the Mucosal Antiviral Response. J Virol 93:10.1128/jvi.01073-19. [CrossRef]
  98. Achille Broggi, Francesca Granucci, Ivan Zanoni (2020); Type III interferons: Balancing tissue tolerance and resistance to pathogen invasion. J Exp Med; 217 (1): e20190295. doi: . [CrossRef]
  99. Nathan C. Layman, Beth M. Tuschhoff, Scott L. Nuismer (2021), Designing transmissible viral vaccines for evolutionary robustness and maximum efficiency, Virus Evolution, Volume 7, Issue 1, veab002, . [CrossRef]
  100. Cao M., Li Y., Song X., Lu Z., Zhai H., Qiu H., Sun Y. (2025). Broad-spectrum vaccines against various and evolving viruses: from antigen design to nanoparticle delivery. J Virol 99:e00997-25. [CrossRef]
  101. Zhang, Q., Cheng, J., Hou, J. et al. Synthetic biology-inspired development of live attenuated influenza vaccines. npj Vaccines 10, 204 (2025). [CrossRef]
  102. Ge, Q., Chen, P., Cheng, Y., & Xiao, Y. (2024). The long road for vaccine development with difficulties and hopes. Emerging Microbes & Infections, 13(1). [CrossRef]
  103. Ye, Y., Pandey, A., Bawden, C. et al. Integrating artificial intelligence with mechanistic epidemiological modeling: a scoping review of opportunities and challenges. Nat Commun 16, 581 (2025). [CrossRef]
  104. 104. Shi Chen, Patrick Robinson, Daniel Janies, Michael Dulin (2020), Four Challenges Associated With Current Mathematical Modeling Paradigm of Infectious Diseases and Call for a Shift, Open Forum Infectious Diseases, Volume 7, Issue 8, ofaa333, . [CrossRef]
  105. Gillum D. R. (2025). A possible turning point for research governance in the life sciences. mSphere, 10(8), e0040725. [CrossRef]
  106. Jewell, N. P. (2024). Artificial Intelligence for Modelling Infectious Disease Epidemics. University of Bristol Preprint. https://research-information.bris.ac.uk/files/446849799/Artificial_Intelligence_for_Modelling_Infectious_Disease_Epidemics_-_Accepted.pdf.
  107. Panda, D.S., Dixit, R., Dixit, A. et al. (2024), Mathematical Model and AI Integration for COVID-19: Improving Forecasting and Policy-Making. SN COMPUT. SCI. 5, 246. [CrossRef]
  108. Figueroa, Ú., Jarry, C., Inzunza, M., Montero, I., Garrido, F., Villagrán, I., ... & Varas, J. (2025). Innovation Meets Practice: A Scalable Simulation-based Methodology for Massive Paracentesis Training. Gastroenterology, 168(5), 865-869. [CrossRef]
  109. Gewaid, H., & Bowie, A. G. (2024). Regulation of type I and type III interferon induction in response to pathogen sensing. Current Opinion in Immunology, 87, 102424. [CrossRef]
  110. Sheen J. K., Kennedy-Shaffer L., Levy M. Z., Metcalf C. J. E. (2025) Design of field trials for the evaluation of transmissible vaccines in animal populations. PLOS Computational Biology 21(2): e1012779. [CrossRef]
  111. The PLOS Computational Biology Staff (2025) Correction: Design of field trials for the evaluation of transmissible vaccines in animal populations. PLoS Comput Biol 21(9): e1013530. [CrossRef]
  112. Bulletin of the Atomic Scientists. (2024). A Framework for Tomorrow’s Pathogen Research. Pathogens Project Report. https://thebulletin.org/pathogens-project/report-2024/ethical-obligations/.
  113. NIH. (2025). Terminating or Suspending Dangerous Gain-of-Function Research. NOT-OD-25-127. https://grants.nih.gov/grants/guide/notice-files/NOT-OD-25-127.html.
  114. White House. (2025). Improving the Safety and Security of Biological Research. Executive Order 14292. https://www.whitehouse.gov/presidential-actions/2025/05/improving-the-safety-and-security-of-biological-research/.
  115. Carp, T. N. (2025). Recent Human Metapneumovirus Outbreak in East Asia: The Time to Shift Immunological Gears is Now. [CrossRef]
  116. Carp, T. N. (2025). Why Creating Transmissible Microbial Interferon Factories May Bring a Promise of a “Golden Era” in Future Human and Animal Health. Preprints. [CrossRef]
  117. Carp, T. N. (2024). Calibrating Human Immunity in the Context of Advanced Microbial Evolution and Self-Camouflaging. Preprints. [CrossRef]
  118. Brodrick, M. (2023, October 27). The Eye of the Hurricane. Open Health Policy. Retrieved from https://www.openhealthpolicy.com/p/the-eye-of-the-hurricane.
  119. ABPI. (2025). The future of vaccines: Innovations in next-generation platforms. Association of the British Pharmaceutical Industry Report. https://www.abpi.org.uk/value-and-access/vaccines/the-future-of-vaccines/.
  120. KGL Team. (2024). UIS Faculty Research on Mathematical Modeling, AI, and the Dynamics of COVID-19 Spread. University of Illinois Springfield Report. https://www.uis.edu/news/uis-faculty-research-mathematical-modeling-ai-and-dynamics-covid-19-spread-0.
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