Genes (Basel). 2025 Apr 28;16(5):515. doi: 10.3390/genes16050515.

ABSTRACT

BACKGROUND/OBJECTIVES: Rhamnolipids (RLs) are biosurfactants with significant industrial and environmental potential, which physicochemical properties depend greatly on their fatty acyl chain composition. This study investigated the impact of genetically modulating the fatty acid synthesis genes fabA and fabZ on RL composition and functionality in Pseudomonas aeruginosa PAO1.

METHODS AND RESULTS: Using temperature-sensitive mutants and suppressor strains for these essential genes, we successfully engineered RLs with altered fatty acyl chain lengths and saturation levels. LC-MS/MS analyses showed that deletion and overexpression of fabA and fabZ significantly shifted RL fatty acid profiles. Functional analyses indicated that these structural changes markedly influenced RL emulsification activity and critical micelle concentration (CMC).

CONCLUSIONS: These findings demonstrate the feasibility of optimizing RL properties through targeted genetic manipulation, offering valuable insights for designing customized biosurfactants for diverse industrial and environmental applications.

PMID:40428336 | DOI:10.3390/genes16050515

Bioengineering (Basel). 2025 Apr 29;12(5):469. doi: 10.3390/bioengineering12050469.

ABSTRACT

Bacteriophages, with their distinctive ability to selectively target host bacteria, stand out as a compelling tool in the realm of drug and gene delivery. Their assembly from proteins and nucleic acids, coupled with their modifiable and biologically unique properties, enables them to serve as efficient and safe delivery systems. Unlike conventional nanocarriers, which face limitations such as non-specific targeting, cytotoxicity, and reduced transfection efficiency in vivo, engineered phages exhibit promising potential to overcome these hurdles and improve delivery outcomes. This review highlights the potential of bacteriophage-based systems as innovative and efficient systems for delivering therapeutic agents. It explores strategies for engineering bacteriophage, categorizes the principal types of phages employed for drug and gene delivery, and evaluates their applications in disease therapy. It provides intriguing details of the use of natural and engineered phages in the therapy of diseases such as cancer, bacterial and viral infections, veterinary diseases, and neurological disorders, as well as the use of phage display technology in generating monoclonal antibodies against various human diseases. Additionally, the use of CRISPR-Cas9 technology in generating genetically engineered phages is elucidated. Furthermore, it provides a critical analysis of the challenges and limitations associated with phage-based delivery systems, offering insights for overcoming these obstacles. By showcasing the advancements in phage engineering and their integration into nanotechnology, this study underscores the potential of bacteriophage-based delivery systems to revolutionize therapeutic approaches and inspire future innovations in medicine.

PMID:40428088 | DOI:10.3390/bioengineering12050469

Biomolecules. 2025 May 2;15(5):656. doi: 10.3390/biom15050656.

ABSTRACT

KIF1A is a neuron-specific kinesin motor responsible for intracellular transport along axons. Pathogenic KIF1A mutations cause KIF1A-associated neurological disorders (KAND), a spectrum of severe neurodevelopmental and neurodegenerative conditions. While individual KIF1A mutations have been studied, how different substitutions at the same residue affect motor function and disease progression remains unclear. Here, we systematically examine the molecular and clinical consequences of mutations at three key motor domain residues-R216, R254, and R307-using single-molecule motility assays and genotype-phenotype associations. We find that different substitutions at the same residue produce distinct molecular phenotypes, and that homodimeric mutant motor properties correlate with developmental outcomes. In addition, we present the first analysis of heterodimeric KIF1A motors-mimicking the heterozygous context in patients-and demonstrate that while heterodimers retain substantial motility, their properties are less predictive of clinical severity than homodimers. These results highlight the finely tuned mechanochemical properties of KIF1A and suggest that dysfunctional homodimers may disproportionately drive the diverse clinical phenotypes observed in KAND. By establishing residue-specific genotype-phenotype relationships, this work provides fundamental insights into KAND pathogenesis and informs targeted therapeutic strategies.

PMID:40427549 | DOI:10.3390/biom15050656

Animals (Basel). 2025 May 19;15(10):1472. doi: 10.3390/ani15101472.

ABSTRACT

Rumen acidosis is a widespread digestive disorder in livestock, causing inflammation and lowering animal performance. Unraveling its molecular mechanisms is vital for improving cattle health and welfare. Circular RNAs (circRNAs) are noncoding RNAs functioning as miRNA or protein sponges. This study employed high-throughput RNA sequencing to identify differentially expressed (DE) circRNAs in subacute rumen acidosis (SARA) in Holstein cattle, revealing 65 DE-circRNAs. We constructed a competitive endogenous RNA (ceRNA) network comprising 57 circRNAs, 14 miRNAs, and 22 mRNAs. Key hub nodes included circRNAs (8:69996068-69996853, 16:2614111-2615445, 5:109525933-109531380, 20:63115665-63116774), miRNAs (bta-miR-146b, bta-miR-181a, bta-miR-223, bta-miR-130b), and mRNAs (SLC2A3, SOCS3, DLC1, ARRDC4). Examination of hub circRNA host genes identified 30 DE transcription factors (TFs). Functional and pathway enrichment analysis pinpointed inflammation and immune response pathways, such as NF-kappa B and TNF signaling. This pioneering study offers the first circRNA expression profile and ceRNA network in SARA cattle, indicating circRNAs' role in inflammation regulation, thus enhancing our understanding of SARA's systems biology and potential treatment strategies.

PMID:40427349 | DOI:10.3390/ani15101472

EMBO J. 2025 May 27. doi: 10.1038/s44318-025-00466-5. Online ahead of print.

ABSTRACT

The three-dimensional (3D) chromatin structure of Epstein-Barr virus (EBV) within host cells and the underlying mechanisms of chromatin interaction and gene regulation, particularly those involving EBV's noncoding RNAs (ncRNAs), have remained incompletely characterized. In this study, we employed state-of-the-art techniques of 3D genome mapping, including protein-associated chromatin interaction analysis with paired-end tag sequencing (ChIA-PET), RNA-associated chromatin interaction technique (RDD), and super-resolution microscopy, to delineate the spatial architecture of EBV in human lymphoblastoid cells. We systematically analyzed EBV-to-EBV (E-E), EBV-to-host (E-H), and host-to-host (H-H) interactions linked to host proteins and EBV RNAs. Our findings reveal that EBV utilizes host CCCTC-binding factor (CTCF) and RNA polymerase II (RNAPII) to form distinct chromatin contact domains (CCDs) and RNAPII-associated interaction domains (RAIDs). The anchors of these chromatin domains serve as platforms for extensive interactions with host chromatin, thus modulating host gene expression. Notably, EBV ncRNAs, especially Epstein-Barr-encoded RNAs (EBERs), target and interact with less accessible regions of host chromatin to repress a subset of genes via the inhibition of RNAPII-associated chromatin loops. This process involves the cofactor nucleolin (NCL) and its RNA recognition motifs, and depletion of either NCL or EBERs alters expression of genes crucial for host infection control, immune response, and cell cycle regulation. These findings unveil a sophisticated interplay between EBV and host chromatin.

PMID:40425856 | DOI:10.1038/s44318-025-00466-5

Nat Med. 2025 May 27. doi: 10.1038/s41591-025-03715-6. Online ahead of print.

ABSTRACT

There is limited evidence supporting the feasibility of using omics and functional technologies to inform treatment decisions. Here we present results from a cohort of 116 melanoma patients in the prospective, multicentric observational Tumor Profiler (TuPro) precision oncology project. Nine independent technologies, mostly at single-cell level, were used to analyze 126 patient samples, generating up to 500 Gb of data per sample (40,000 potential markers) within 4 weeks. Among established and experimental markers, the molecular tumor board selected 54 to inform its treatment recommendations. In 75% of cases, TuPro-based data were judged to be useful in informing recommendations. Patients received either standard of care (SOC) treatments or highly individualized, polybiomarker-driven treatments (beyond SOC). The objective response rate in difficult-to-treat palliative, beyond SOC patients (n = 37) was 38%, with a disease control rate of 54%. Progression-free survival of patients with TuPro-informed therapy decisions was 6.04 months, (95% confidence interval, 3.75-12.06) and 5.35 months (95% confidence interval, 2.89-12.06) in ≥third therapy lines. The proof-of-concept TuPro project demonstrated the feasibility and relevance of omics-based tumor profiling to support data-guided clinical decision-making. ClinicalTrials.gov identifier: NCT06463509 .

PMID:40425842 | DOI:10.1038/s41591-025-03715-6

Commun Biol. 2025 May 27;8(1):815. doi: 10.1038/s42003-025-08109-5.

ABSTRACT

Biological methods are a promising route for the environmentally-friendly production of rare earth elements (REE), which are essential for sustainable energy and defense technologies. In earlier work we identified the key genetic mechanisms contributing to the REE-bioleaching capability of Gluconobacter oxydans B58. Here we have targeted two of these mechanisms to generate a high-efficiency bioleaching strain of G. oxydans. Disruption of the phosphate-specific transport system through a clean deletion of pstS constitutively turns on the phosphate starvation response, yielding a much more acidic biolixiviant, and increasing bioleaching by up to 30%. Coupling knockout of pstS with the over-expression of the mgdh membrane-bound glucose dehydrogenase gene using the P112 promoter (strain G. oxydans ΔpstS, P112:mgdh) reduces biolixiviant pH by 0.39 units; increases REE-bioleaching by 53% at a pulp density of 10% and increases it by 73% at a pulp density of 1%.

PMID:40425722 | DOI:10.1038/s42003-025-08109-5

NPJ Sci Food. 2025 May 27;9(1):87. doi: 10.1038/s41538-025-00443-6.

ABSTRACT

Grape polyphenols (GPs) are rich in B-type proanthocyanidins, which promote metabolic resilience. Longitudinal metabolomic, metagenomic, and metaproteomic changes were measured in 27 healthy subjects supplemented with soy protein isolate (SPI, 40 g per day) for 5 days followed by GPs complexed to SPI (GP-SPI standardized to 5% GPs, 40 g per day) for 10 days. Fecal, urine, and/or fasting blood samples were collected before supplementation (day -5), after 5 days of SPI (day 0), and after 2, 4 and 10 days of GP-SPI. Most multi-omic changes observed after 2 and/or 4 days of GP-SPI intake were temporary, returning to pre-supplementation profiles by day 10. Shotgun metagenomics sequencing provided insights that could not be captured with 16S rRNA amplicon sequencing. Notably, 10 days of GP-SPI decreased fasting blood glucose and increased serum hyocholic acid (HCA), a glucoregulatory bile acid, which negatively correlated with one gut bacterial guild. In conclusion, GP-induced suppression of a bacterial guild may lead to higher HCA and lower fasting blood glucose.

PMID:40425565 | DOI:10.1038/s41538-025-00443-6

Nat Commun. 2025 May 27;16(1):4889. doi: 10.1038/s41467-025-59564-x.

ABSTRACT

Systematic inference of enzyme activity in human tumors is key to understanding cancer progression and resistance to therapy. However, standard protein or transcript abundances are blind to the activity status of the measured enzymes, regulated, for example, by active-site amino acid mutations or post-translational protein modifications. Current methods for activity-based proteome profiling (ABPP), which combine mass spectrometry (MS) with chemical probes, quantify the fraction of enzymes that are catalytically active. Here, we describe depletion-dependent ABPP (dd-ABPP) combined with automated SWATH/DIA-MS, which simultaneously determines three molecular layers of studied enzymes: i) catalytically active enzyme fractions, ii) enzyme and background protein abundances, and iii) context-dependent enzyme-protein interactions. We demonstrate the utility of the method in advanced lung adenocarcinoma (LUAD) by monitoring nearly 4000 protein groups and 200 serine hydrolases (SHs) in tumor and adjacent tissue sections routinely collected for patient histopathology. The activity profiles of 23 SHs and the abundance of 59 proteins associated with these enzymes retrospectively classified aggressive LUAD. The molecular signature revealed accelerated lipoprotein depalmitoylation via palmitoyl(protein)hydrolase activities, further confirmed by excess palmitate and its metabolites. The approach is universal and applicable to other enzyme families with available chemical probes, providing clinicians with a biochemical rationale for tumor sample classification.

PMID:40425563 | DOI:10.1038/s41467-025-59564-x

NPJ Syst Biol Appl. 2025 May 27;11(1):56. doi: 10.1038/s41540-025-00528-8.

ABSTRACT

Evolutionary cancer therapy (ECT) delays or forestalls the progression of metastatic cancer by adjusting treatment based on individual patient and disease characteristics. Clinical implementation of ECT can improve patient outcomes but faces technical and cultural challenges. To address those, we propose a systems approach incorporating systems modeling, problem structuring, and stakeholder engagement. This approach identifies and addresses barriers to implementation, ensuring the feasibility of ECT in clinical practice and enabling better metastatic cancer care.

PMID:40425536 | DOI:10.1038/s41540-025-00528-8

J R Soc Interface. 2025 May;22(226):20240852. doi: 10.1098/rsif.2024.0852. Epub 2025 May 28.

ABSTRACT

The long non-coding RNA metastasis-associated lung adenocarcinoma transcript 1 (lncRNA MALAT1) and microRNA-145-5p (miR-145) axis play a pivotal role in regulating drug resistance, apoptosis and senescence in non-small cell lung cancer (NSCLC). MALAT1 drives drug resistance by suppressing miR-145 and activating MUC1, thereby inhibiting ferroptosis; however, its precise role in regulating ferroptosis in NSCLC remains unclear. Therefore, we propose a computational modelling approach to unravel the impact of the MALAT1/miR-145 axis on ferroptosis and drug resistance, to identify potential therapeutic strategies that promote ferroptosis. Using Boolean logic and a stochastic updating scheme, we developed and validated a robust regulatory model that encompasses ferroptosis, apoptosis, senescence and drug resistance pathways. The model, based on extensive literature and validated through gain- and loss-of-function perturbations, demonstrated strong alignment with observed clinical data that were not included in its construction. Our analysis identified three previously unreported feedback loops, miR-145/Wip1/p53, miR-145/Myc/MALAT1 and miR-145/MUC1/BMI1, establishing miR-145 as a central regulator in NSCLC. Perturbations targeting MALAT1 and wild-type p53-induced phosphatase 1 (Wip1) revealed potential therapeutic opportunities, with miR-145 activation emerging as a promising strategy to induce ferroptosis and overcome drug resistance. These findings highlight the MALAT1/miR-145 axis as a transformative therapeutic target, presenting a computational foundation to advance NSCLC treatment strategies.

PMID:40425041 | DOI:10.1098/rsif.2024.0852

PLoS Biol. 2025 May 27;23(5):e3003208. doi: 10.1371/journal.pbio.3003208. Online ahead of print.

ABSTRACT

Bacteria deploy a diverse arsenal of toxic effectors to antagonize competitors, profoundly influencing the composition of microbial communities. Previous studies have identified an interbacterial toxin predicted to exhibit proteolytic activity that is broadly distributed among gram-negative bacteria. However, the precise mechanism of intoxication remains unresolved. Here, we demonstrate that one such protease toxin from Escherichia coli, Cpe1, disrupts DNA replication and chromosome segregation by cleaving conserved sequences within the ATPase domain of type II DNA topoisomerases GyrB and ParE. This cleavage effectively inhibits topoisomerase-mediated relaxation of supercoiled DNA, resulting in impaired bacterial growth. Cpe1 belongs to the papain-like cysteine protease family and is associated with toxin delivery pathways, including the type VI secretion system and contact-dependent growth inhibition. The structure of Cpe1 in complex with its immunity protein reveals a neutralization mechanism involving competitive substrate binding rather than active site occlusion, distinguishing it from previously characterized effector-immunity pairs. Our findings unveil a unique mode of interbacterial intoxication and provide insights into how bacteria protect themselves from self-poisoning by protease toxins.

PMID:40424468 | DOI:10.1371/journal.pbio.3003208

Sci Signal. 2025 May 27;18(888):eadu3794. doi: 10.1126/scisignal.adu3794. Epub 2025 May 27.

ABSTRACT

Delineating the mechanisms that control the movement of cells is central to understanding diverse physiological and pathophysiological processes. The transcriptional coactivator YAP is important during development and associated with cancer metastasis. Here, we found that YAP promoted cell migration by modulating a Rho family guanosine triphosphatase (GTPase) switch involving Rac1 and RhoA, which are key regulators of cytoskeletal dynamics. YAP transcriptionally transactivated the gene encoding the Rac1 guanine nucleotide exchange factor TRIO by directly binding to its intronic enhancer. This led to the activation of Rac1 and inhibition of RhoA, which increased cell migration and invasion in vitro and in vivo. This YAP-dependent program was observed across many cell types, including human breast epithelial cells and astrocytes, but it was particularly enhanced in a patient-specific manner in glioblastoma (GBM), the most common malignant brain tumor. Additionally, YAP-TRIO signaling activated STAT3, a transcription factor implicated in invasive growth in cancer, suggesting potential for cross-talk with this pathway to exacerbate invasive behavior. Clinically, hyperactivation of YAP, TRIO, and STAT3 gene signatures in GBM were associated with poor survival outcomes in patients. Our findings suggest that the YAP-TRIO-Rho-GTPase signaling network regulates invasive cell spread in both physiological and pathological contexts.

PMID:40424361 | DOI:10.1126/scisignal.adu3794

Elife. 2025 May 27;13:RP94029. doi: 10.7554/eLife.94029.

ABSTRACT

Despite the recent breakthrough of AlphaFold (AF) in the field of protein sequence-to-structure prediction, modeling protein interfaces and predicting protein complex structures remains challenging, especially when there is a significant conformational change in one or both binding partners. Prior studies have demonstrated that AF-multimer (AFm) can predict accurate protein complexes in only up to 43% of cases (Yin et al., 2022). In this work, we combine AF as a structural template generator with a physics-based replica exchange docking algorithm to better sample conformational changes. Using a curated collection of 254 available protein targets with both unbound and bound structures, we first demonstrate that AF confidence measures (pLDDT) can be repurposed for estimating protein flexibility and docking accuracy for multimers. We incorporate these metrics within our ReplicaDock 2.0 protocol to complete a robust in silico pipeline for accurate protein complex structure prediction. AlphaRED (AlphaFold-initiated Replica Exchange Docking) successfully docks failed AF predictions, including 97 failure cases in Docking Benchmark Set 5.5. AlphaRED generates CAPRI acceptable-quality or better predictions for 63% of benchmark targets. Further, on a subset of antigen-antibody targets, which is challenging for AFm (20% success rate), AlphaRED demonstrates a success rate of 43%. This new strategy demonstrates the success possible by integrating deep learning-based architectures trained on evolutionary information with physics-based enhanced sampling. The pipeline is available at https://github.com/Graylab/AlphaRED.

PMID:40424178 | DOI:10.7554/eLife.94029

J Chem Inf Model. 2025 May 27. doi: 10.1021/acs.jcim.4c02363. Online ahead of print.

ABSTRACT

Effective drug safety assessment, guided by the 3R principle (Replacement, Reduction, Refinement) to minimize animal testing, is critical in early drug development. Drug-induced liver injury (DILI), particularly drug-induced cholestasis (DIC), remains a major challenge. This study introduces a computational method for predicting DIC by integrating PubChem substructure fingerprints with biological data from liver-expressed targets and pathways, alongside nine hepatic transporter inhibition models. To address class imbalance in the public cholestasis data set, we employed undersampling, a technique that constructs a small and robust consensus model by evaluating distinct subsets. The most effective baseline model, which combined PubChem substructure fingerprints, pathway data and hepatic transporter inhibition predictions, achieved a Matthews correlation coefficient (MCC) of 0.29 and a sensitivity of 0.79, as validated through 10-fold cross-validation. Subsequently, target prediction using four publicly available tools was employed to enrich the sparse compound-target interaction matrix. Although this approach showed lower sensitivity compared to experimentally derived targets and pathways, it highlighted the value of incorporating specific systems biology related information. Feature importance analysis identified albumin as a potential target linked to cholestasis within our predictive model, suggesting a connection worth further investigation. By employing an expanded consensus model and applying probability range filtering, the refined method achieved an MCC of 0.38 and a sensitivity of 0.80, thereby enhancing decision-making confidence. This approach advances DIC prediction by integrating biological and chemical descriptors, offering a reliable and explainable model.

PMID:40421892 | DOI:10.1021/acs.jcim.4c02363

Stroke. 2025 May 27. doi: 10.1161/STROKEAHA.124.050033. Online ahead of print.

NO ABSTRACT

PMID:40421566 | DOI:10.1161/STROKEAHA.124.050033

PeerJ. 2025 May 23;13:e19487. doi: 10.7717/peerj.19487. eCollection 2025.

ABSTRACT

OBJECTIVE: Transfer RNA-derived small RNAs (tsRNAs) are emerging regulators of gene expression in response to abiotic stress. This review aims to summarize recent advances in the classification, biogenesis, and biological functions of tsRNAs, with a focus on their roles in plant stress responses and the methodologies for investigating these molecules.

METHODS: We conducted a comprehensive literature search across PubMed, Web of Science, and Google Scholar using keywords such as "tRNA-derived small RNAs", "abiotic stress", "plant gene regulation", and "RNA sequencing". Studies were selected based on their relevance to tsRNA biogenesis pathways, stress-responsive mechanisms, and functional validation in plant systems. Classification of tsRNAs was performed according to cleavage site specificity and nucleotide length. Bioinformatic tools and experimental approaches for tsRNA identification, target prediction, and functional validation were evaluated.

RESULTS: tsRNAs are categorized into two main types: tRNA-derived stress-induced RNAs (tiRNAs; 29-50 nt) and tRNA-derived fragments (tRFs; 14-40 nt). tiRNAs arise from anticodon loop cleavage by RNase A/T2, while tRFs are generated via Dicer-dependent or -independent pathways. These molecules regulate gene expression at transcriptional, post-transcriptional, and translational levels by interacting with AGO proteins, displacing translation initiation factors, and modulating stress granule assembly. In plants, tsRNAs respond dynamically to abiotic stresses (e.g., drought, salinity, heat), influencing stress signaling pathways and epigenetic modifications. Advanced sequencing techniques (e.g., cP-RNA-seq, RtcB sRNA-seq) and databases (PtRFdb, tRFanalyzer) have facilitated tsRNA discovery and functional annotation.

CONCLUSIONS: tsRNAs represent a versatile class of regulatory molecules in plant stress biology. Their ability to fine-tune gene expression underpins adaptive responses to environmental challenges. Future research should prioritize standardized methodologies for tsRNA profiling, elucidation of stress-specific biogenesis mechanisms, and exploration of their potential as biomarkers or therapeutic targets for crop improvement. Integrating tsRNA research with systems biology approaches will deepen our understanding of plant resilience mechanisms.

PMID:40421365 | PMC:PMC12105621 | DOI:10.7717/peerj.19487

Small Methods. 2025 May 27:e2500572. doi: 10.1002/smtd.202500572. Online ahead of print.

ABSTRACT

Single-cell technologies have revolutionized the understanding of cellular dynamics by allowing researchers to investigate individual cell responses under various conditions, such as comparing diseased versus healthy states. Many differential abundance methods have been developed in this field, however, the understanding of the gene signatures obtained from those methods is often incomplete, requiring the integration of cell type information and other biological factors to yield interpretable and meaningful results. To better interpret the gene signatures generated in the differential abundance analysis, iDAS is developed to classify the gene signatures into multiple categories. When applied to melanoma single-cell data with multiple cell states and treatment phenotypes, iDAS identified cell state- and treatment phenotype-specific gene signatures, as well as interaction effect-related gene signatures with meaningful biological interpretations. The iDAS model is further applied to a longitudinal study and spatially resolved omics data to demonstrate its versatility in different analytical contexts. These results demonstrate that the iDAS framework can effectively identify robust, cell-state specific gene signatures and is versatile enough to accommodate various study designs, including multi-factor longitudinal and spatially resolved data.

PMID:40420636 | DOI:10.1002/smtd.202500572

Mol Plant. 2025 May 26:S1674-2052(25)00171-6. doi: 10.1016/j.molp.2025.05.012. Online ahead of print.

NO ABSTRACT

PMID:40420481 | DOI:10.1016/j.molp.2025.05.012

CPT Pharmacometrics Syst Pharmacol. 2025 May 26. doi: 10.1002/psp4.70041. Online ahead of print.

ABSTRACT

The unprecedented effort to cope with the COVID-19 pandemic has unlocked the potential of mRNA vaccines as a powerful technology, set to become increasingly pervasive in the years to come. As in other areas of drug development, mathematical modeling is a pivotal tool to support and expedite the mRNA vaccine development process. This study introduces a Quantitative Systems Pharmacology (QSP) model that captures key immune responses following mRNA vaccine administration, encompassing both tissue-level and molecular-level events. The model mechanistically describes the biological processes from the uptake of mRNA by antigen-presenting cells at the injection site to the subsequent release of antibodies into the bloodstream. This two-layer model represents a first attempt to link the molecular mechanisms leading to antigen expression with the immune response, paving the way for the future integration of specific vaccine attributes, such as mRNA sequence features and nanotechnology-based delivery systems. Calibrated specifically for the BNT162b2 SARS-CoV-2 vaccine, the model has undergone successful validation across various dosing regimens and administration schedules. The results underscore the model's effectiveness in optimizing dosing strategies and highlighting critical differences in immune responses, particularly among low-responder groups such as the elderly. Furthermore, the model's adaptability has been demonstrated through its calibration for other mRNA vaccines, such as the Moderna mRNA-1273 vaccine, emphasizing its versatility and broad applicability in mRNA vaccine research and development.

PMID:40420402 | DOI:10.1002/psp4.70041