Generation Of Antibodies Research Articles

HMGA1 influence on iron-induced cell death in Tfh cells of SLE patients

The autoimmune disorder known as Systemic Lupus Erythematosus (SLE) exhibits intricate features with abnormal immune responses leading to tissue injury. The generation of antibodies and the disruption of immune regulation heavily depend on the pivotal function of T follicular helper (Tfh) cells. Iron dysregulation is significant in autoimmune diseases, impacting immune cell function and disease progression. Our study investigates the role of the HMGA1/EZH2/STAT3/GPX4 axis in modulating Tfh cells and iron homeostasis in SLE. Abnormal Tfh cell populations in SLE patients demonstrate reduced susceptibility to iron-induced cell death, with HMGA1 identified as a key player in Tfh cell proliferation and sensitivity to iron-induced death. Experimental interventions reveal the inhibitory role of the HMGA1 axis in Tfh cells' susceptibility to iron-induced death, suggesting therapeutic avenues for SLE and related autoimmune disorders. Our study underscores the importance of iron homeostasis in autoimmune conditions, providing novel insights and treatment strategies for further research in this field.Graphical abstract1. HMGA1 suppresses iron-induced cell death in Tfh cells of SLE patients.2. The HMGA1/EZH2/STAT3/GPX4 axis maintains Tfh cell viability, critical in SLE pathogenesis.3. Targeting the HMGA1 pathway offers new therapeutic potential for SLE.

Helicobacter pylori and rheumatoid arthritis: Investigation of relation from traditional Chinese medicine.

Rheumatoid arthritis (RA) is an autoimmune condition that predominantly affects synovial joints, manifesting with joint swelling, pain, and stiffness. In advanced stages, unchecked inflammation can inflict damage on bone and cartilage, resulting in disabilities and deformities of the joints. Additionally, systemic and extra-articular complications may arise due to the consequences of uncontrolled inflammation. Helicobacter pylori (H. pylori) is one of the most prevalent chronic bacterial infections in humans. This microorganism is a spiral-shaped, flagellated, microaerophilic gram-negative bacterium. Prolonged exposure leads to the activation of the immune system, with infected gastric mucosa epithelial cells continuously producing cytokines. This production, in turn, triggers the generation of antibodies as well as T Helper 1 and T Helper 2 effector T cells. The persistent antigenic stimulation resulting from H. pylori infection could lead to the progression of autoimmune diseases. Numerous clinical and pharmacological trials have illustrated the efficacy of traditional Chinese medicine against H. pylori. This review aims to delve into the connection between H. pylori and rheumatoid arthritis so as understand the pathogenesis. The concluding section of this review explores the interplay of Chinese medicine and Helicobacter pylori concerning rheumatoid arthritis.

DDO-adjuvanted influenza A virus nucleoprotein mRNA vaccine induces robust humoral and cellular type 1 immune responses and protects mice from challenge.

A challenge in viral vaccine development is to produce vaccines that generate both neutralizing antibodies to prevent infection and cytotoxic CD8+ T-cells that target conserved viral proteins and can eliminate infected cells to control virus spread. mRNA technology offers an opportunity to design vaccines based on conserved CD8-targeting epitopes, but achieving robust antigen-specific CD8+ T-cells remains a challenge. Here, we tested the viral-derived oligonucleotide DDO268 as an adjuvant in the context of a model influenza A virus (IAV) nucleoprotein (NP) mRNA vaccine in C57BL/6 mice. DDO268 when co-packaged with mRNA in lipid nanoparticles is sensed by RIG I-like receptors and safely induces local type I interferon (IFN) production followed by dendritic cells type 1 activation and migration to the draining lymph nodes. This early response triggered by DDO268 improved the generation of IgG2c antibodies and antigen-specific Th1 CD4+ and CD8+ T-cells (IFNγ+TNFα+IL2+) that provided enhanced protection against lethal IAV challenge. In addition, the inclusion of DDO268 reduced the antigen dose required to achieve protection. These results highlight the potential of DDO268 as an effective mRNA vaccine adjuvant and show that an IAV NP mRNA/DDO268 vaccine is a promising approach for generating protective immunity against conserved internal IAV epitopes.IMPORTANCEVaccines that generate neutralizing antibodies and cytotoxic CD8+ T-cells targeting conserved epitopes are ideal for effective protection against viruses. mRNA vaccines combined with the right adjuvant offer a promising solution to this challenge. We show that the virus-derived oligonucleotide DDO268 enhances antibody and T-cell responses to an influenza A virus (IAV) nucleoprotein mRNA vaccine in mice. DDO268 safely induces local type I interferon production and stimulates dendritic cell activation providing enhanced protection against IAV challenge. In addition, the adjuvant activity of DDO268 allows for the use of lower antigen doses during vaccination.

Antibody Recognition Profile-Aided Hapten Design to Modulate Antibody Generation with Anticipated Performance for Immunoassay Development.

The hapten design to chemical compound currently considered only structural aspects of targets may suffer from the failure of antibody generation with anticipated performances, especially for broad-specific antibodies. To address the problem, this study proposed a novel strategy, named antibody recognition profile-aided hapten design (ARPHD), based on clues from both reported antibodies, haptens, and targets after uncovering antibody recognition profiles using fluorfenicol (FF) and fluorfenicol amine (FFA) as model analytes in this work. Specifically, we confirmed that the fluorine atom promoted the generation of antibodies to FFA, while the -COCHCl2 moiety was unfavorable for inducing broad-specific antibodies to FF and FFA. Based on the structural information from ARPHD, four novel haptens without -COCHCl2 and containing a fluorine atom are intentionally designed, then identified by computational chemistry and animal immunization, successfully inducing antibodies to FF and FFA with uniform IC50 values of 3.09 and 3.75 ng mL-1. The explanation of molecular mechanisms from the obtained antibodies has supported the scientific base behind ARPHD, and we also found that the light chain of the antibody contributed an important role in differential recognition of the antibody. Finally, an indirect competitive ELISA (icELISA) was developed for the simultaneous detection of FF and FFA in river water and animal-derived food with a LOD of 2.24-14.6 μg kg-1, which has never been achieved before. The study demonstrated that the ARPHD we proposed could rationally guide the design of haptens that modulate the generation of antibodies with appreciated performances and easily be extended to other chemical compounds as a versatile platform.

SARS CoV-2 Delta Variant Spike Protein: Structure, Mechanism, and Docking Interaction with Antiviral Ligands from the Plants of the Phyllanthus Genus

Abstract: An abrupt outbreak of "Severe Acute Respiratory Syndrome Coronavirus 2" was first identified in Wuhan City, Hubei Province, China, in December 2019, which was later disseminated globally. Individuals afflicted with this highly transmissible virus contribute to a significant public health crisis. The lack of specific vaccinations and antiviral medications for nCoV-2019, together with the emergence of mutations in the genome of the virus, necessitates a multifaceted approach to drug design and discovery for COVID-19. A comprehensive worldwide supervision plan is essential for the accurate forecast and prevention of viral infections. The SARS-CoV-2 spike (S) protein plays a crucial role in viral binding, fusion, and entrance, hence influencing the generation and evolution of antibodies and vaccines. The receptor binding domain (RBD) of the SARS-CoV-2 spike protein exhibits a significant affinity for human angiotensin-converting enzyme 2 (ACE2) receptors. It encompasses diverse mutations in the N-terminal domain (NTD) and the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein, enhancing immunological efficacy. The B.1.617.2 mutant, also known as the Delta variation, is expected to spread more rapidly than earlier versions. Thus, in this study, we have evaluated the structural characteristics of the SARS-CoV-2 spike protein and the human ACE2 protein and their interactions and examined putative SPIKE-ACE2 protein-protein inhibitors derived from the phytocompounds of Phyllanthus species. This is the crucial aspect for the advancement of economical clinical trials of individual plant components for the treatment of viral diseases.

Transgenic Schizochytrium as a Promising Oral Vaccine Carrier: Potential Application in the Aquaculture Industry.

Schizochytrium limacinum SR21, a kind of eukaryotic heterotrophic organism rich in unsaturated fatty acids, is an emerging microbial alternative to fish oil. The dietary inclusion of 15% SR21 was optimal for the growth performance of zebrafish. Previous studies demonstrated that fructose-1,6-bisphosphate aldolase (FBA) of Edwardsiella tarda is a valuable broad-spectrum antigen against various pathogens in aquaculture (e.g., Aeromonas hydrophila, Vibro anguillarum, Vibro harveyi, Vibro alginolyticus). We pioneered the development of stable S. limacinum SR21 transformants expressing the antigen protein FBA, exploring their potential as a novel oral vaccine for the aquaculture industry. The model animal zebrafish (Danio rerio) and ornamental fish koi carp (Cyprinus carpio koi) were harnessed to assess the immunoprotective effect, respectively. According to the quantitative expression analysis, zebrafish fed with recombinant Schizochytrium expressing FBA exhibited specific immune responses in the intestine. The expression levels of MHC-I and MHC-II, involved in cell-mediated adaptive immune responses, were significantly upregulated on the 14th and 28th days post-immunization. Additionally, the expression of highly specialized antibody genes IgZ1 and IgZ2 in mucosal immunity were significantly triggered on the 14th day post-immunization. Feeding koi carp with recombinant S. limacinum SR21-FBA increased the production of myeloperoxidase and FBA-specific antibodies in the sera. Furthermore, the sera of koi fed with recombinant S. limacinum SR21-FBA exhibited significant bactericidal activities against pathogen E. tarda. Thus, S. limacinum SR21 is a natural and highly promising oral vaccine carrier that not only provides essential nutrients as a functional feed ingredient but also offers specific immune protection to aquatic animals. This dual application is vital for promoting the sustainable development of the aquaculture industry.

Characterization of differentially regulated carboxypeptidase (metallopeptidase M32) protein in Miltefosine resistant Leishmania donovani parasites.

Carboxypeptidase, a member of the metallopeptidase M32 family, catalyses the C-terminal hydrolysis of a variety of peptides and proteins in the presence of metal ions. To characterize Leishmania donovani carboxypeptidase (LdCP) in miltefosine (MIL) drug-resistant parasites. We performed the MTT assay and cell cycle analysis to confirm the MIL resistance of clinical isolates. LdCP gene was cloned and expressed in E. coli Artic strain. The purified LdCP protein was used for antibody generation and biochemical characterization. MTT assay and cell cycle analysis revealed that all three isolates exhibit MIL resistance. LdCP constitutively expressed in both promastigote and amastigote stages of parasites, and its activity increased 2-3 fold in MIL-resistant parasites. LdCP has high α-helical content at physiological pH and temperature. The protein is quite thermostable with a Tm of 63°C and susceptible to chemical denaturation, with 50% unfolding induced by 3.59M urea or 0.31M guanidine hydrochloride (GdmCl). LC-MS/MS study reveals that LdCP interacts with membrane-associated proteins that have ATP binding sites and involved in protein phosphorylation. To our knowledge, this is the first study to characterize the carboxypeptidase of L. donovani that appears to contribute to the development of MIL resistance parasites.

Imaging flow cytometry as a novel approach for the diagnosis of heparin-induced thrombocytopenia.

Heparin-induced thrombocytopenia (HIT) is an adverse reaction characterized by anti-PF4-heparin antibody generation and hypercoagulability. Imaging flow cytometry (IFC) provides a detailed morphological analysis of platelets, which change upon activation. We evaluated IFC-derived morphometric features to detect platelet activation and developed a functional assay for HIT diagnosis. We analysed blood samples from 42 patients with suspected HIT and extracted platelet size, shape and texture features using IFC. The morphological features were compared with CD62P expression, light transmission aggregometry (LTA) and a serotonin release assay (SRA) in terms of their ability to predict a HIT diagnosis. Five IFC-derived morphological features (area, circularity, contrast, diameter and major axis) significantly distinguished resting from activated platelets. The major axis feature performed best for HIT diagnosis, with a sensitivity of 89.3% and a specificity of 92.9% versus functional assays (LTA/SRA); this diagnostic performance was similar to that of CD62P expression on the same platelet donors. The area and diameter had similar specificity (92.9%) and a slightly lower sensitivity (85.7%). The morphological features associated with platelet activation might be effective markers for the diagnosis of HIT, matching platelet CD62P expression assay performance. The high-throughput IFC exploration of platelet activation offers new perspectives in label-free analysis and time-saving.

Epigenetic Regulation of Immune Cells in Health and Disease: A Comprehensive Review

Epigenetic regulation plays a crucial role in controlling gene expression in immune cells, influencing their development, differentiation, and function in both health and disease. Epigenetic mechanisms, including DNA methylation, histone modifications, and non-coding RNAs, act as dynamic regulators that allow immune cells to respond to environmental cues, ensuring precise immune responses. In innate immune cells, such as macrophages and dendritic cells, these modifications dictate functional plasticity and antigen-presenting capabilities. In adaptive immune cells, including T cells and B cells, epigenetic changes control lineage commitment, cytokine production, and antibody generation. Dysregulation of these processes can lead to immune-related diseases, such as autoimmune disorders, cancer, and chronic inflammatory conditions. In autoimmune diseases like systemic lupus erythematosus and rheumatoid arthritis, aberrant epigenetic modifications contribute to the loss of immune tolerance and chronic inflammation. In cancer, altered epigenetic states in both immune cells and tumor cells promote immune evasion and tumor progression. The understanding of these mechanisms has opened new therapeutic avenues, with epigenetic therapies being explored for reprogramming immune responses. This review highlights the role of epigenetic regulation in immune cell function, discusses its dysregulation in disease, and explores its therapeutic potential for improving immune-related outcomes. Keywords: Epigenetics, Immune cells, DNA methylation, Histone modifications, Autoimmune diseases, Cancer

Expanding the landscape of antibody discovery.

Library:library screening technologies hold substantial promise for paired antibody:antigen discovery, but challenges have persisted. In this issue of Cell Reports Methods, Wagner etal. introduce a method that combines antibody-ribosome-mRNA complexes, antigen cell surface display, and single-cell RNA sequencing to successfully screen diverse antibody gene libraries against a library of viral receptor proteins.

Integrating Interpretability in Machine Learning and Deep Neural Networks: A Novel Approach to Feature Importance and Outlier Detection in COVID-19 Symptomatology and Vaccine Efficacy.

In this study, we introduce a novel approach that integrates interpretability techniques from both traditional machine learning (ML) and deep neural networks (DNN) to quantify feature importance using global and local interpretation methods. Our method bridges the gap between interpretable ML models and powerful deep learning (DL) architectures, providing comprehensive insights into the key drivers behind model predictions, especially in detecting outliers within medical data. We applied this method to analyze COVID-19 pandemic data from 2020, yielding intriguing insights. We used a dataset consisting of individuals who were tested for COVID-19 during the early stages of the pandemic in 2020. The dataset included self-reported symptoms and test results from a wide demographic, and our goal was to identify the most important symptoms that could help predict COVID-19 infection accurately. By applying interpretability techniques to both machine learning and deep learning models, we aimed to improve understanding of symptomatology and enhance early detection of COVID-19 cases. Notably, even though less than 1% of our cohort reported having a sore throat, this symptom emerged as a significant indicator of active COVID-19 infection, appearing 7 out of 9 times in the top four most important features across all methodologies. This suggests its potential as an early symptom marker. Studies have shown that individuals reporting sore throat may have a compromised immune system, where antibody generation is not functioning correctly. This aligns with our data, which indicates that 5% of patients with sore throats required hospitalization. Our analysis also revealed a concerning trend of diminished immune response post-COVID infection, increasing the likelihood of severe cases requiring hospitalization. This finding underscores the importance of monitoring patients post-recovery for potential complications and tailoring medical interventions accordingly. Our study also raises critical questions about the efficacy of COVID-19 vaccines in individuals presenting with sore throat as a symptom. The results suggest that booster shots might be necessary for this population to ensure adequate immunity, given the observed immune response patterns. The proposed method not only enhances our understanding of COVID-19 symptomatology but also demonstrates its broader utility in medical outlier detection. This research contributes valuable insights to ongoing efforts in creating interpretable models for COVID-19 management and vaccine optimization strategies. By leveraging feature importance and interpretability, these models empower physicians, healthcare workers, and researchers to understand complex relationships within medical data, facilitating more informed decision-making for patient care and public health initiatives.

Distinct Requirements for CD4+ T Cell Help for Immune Responses Induced by mRNA and Adenovirus-Vector SARS-CoV-2 Vaccines.

CD4+ T cells have been established as central orchestrators of cellular and humoral immune responses to infection or vaccination. However, the need for CD4+ T cell help to generate primary CD8+ T cell responses is variable depending on the infectious agent or vaccine and yet consistently required for the recall of CD8+ T cell memory responses or antibody responses. Given the deployment of new vaccine platforms such as nucleoside-modified mRNA vaccines, we sought to elucidate the requirement for CD4+ T cell help in the induction of cellular and antibody responses to mRNA and adenovirus (Ad)-vectored vaccines against SARS-CoV-2. Using antibody-mediated depletion of CD4+ T cells in a mouse immunization model, we observed that CD4+ T cell help was dispensable for both primary and secondary CD8+ T cell responses to the BNT162b2 and mRNA-1273 mRNA vaccines but required for the AZD1222 Ad-vectored vaccine. Nonetheless, CD4+ T cell help was needed by both mRNA and Ad-vectored vaccine platforms for the generation of antibodies, demonstrating the centrality of CD4+ T cells in vaccine-induced protective immunity against SARS-CoV-2. Ultimately, this highlights the shared and distinct regulation of humoral and cellular responses induced by these vaccine platforms.

Antibody Data Analysis from Diverse Immune Libraries.

Antibody functional screening studies and next-generation sequencing require careful processing and interpretation of sequence data for optimal results. Here, we provide a detailed protocol for the functional analysis of antibody gene data, including antibody repertoire quantification and functional mapping of high-throughput screening data based on enrichment ratio values, which are a simple way to determine the enrichment of each sequenced antibody after sorting a display library against desired antigens. This protocol enables a user to apply a set of simple yet powerful bioinformatic tools for high-throughput analysis and interpretation of antibody data that is especially well suited for display library screening and for antibody discovery applications.

Deep learning-based design and experimental validation of a medicine-like human antibody library.

Antibody generation requires the use of one or more time-consuming methods, namely animal immunization, and in vitro display technologies. However, the recent availability of large amounts of antibody sequence and structural data in the public domain along with the advent of generative deep learning algorithms raises the possibility of computationally generating novel antibody sequences with desirable developability attributes. Here, we describe a deep learning model for computationally generating libraries of highly human antibody variable regions whose intrinsic physicochemical properties resemble those of the variable regions of the marketed antibody-based biotherapeutics (medicine-likeness). We generated 100000 variable region sequences of antigen-agnostic human antibodies belonging to the IGHV3-IGKV1 germline pair using a training dataset of 31416 human antibodies that satisfied our computational developability criteria. The in-silico generated antibodies recapitulate intrinsic sequence, structural, and physicochemical properties of the training antibodies, and compare favorably with the experimentally measured biophysical attributes of 100 variable regions of marketed and clinical stage antibody-based biotherapeutics. A sample of 51 highly diverse in-silico generated antibodies with >90th percentile medicine-likeness and > 90% humanness was evaluated by two independent experimental laboratories. Our data show the in-silico generated sequences exhibit high expression, monomer content, and thermal stability along with low hydrophobicity, self-association, and non-specific binding when produced as full-length monoclonal antibodies. The ability to computationally generate developable human antibody libraries is a first step towards enabling in-silico discovery of antibody-based biotherapeutics. These findings are expected to accelerate in-silico discovery of antibody-based biotherapeutics and expand the druggable antigen space to include targets refractory to conventional antibody discovery methods requiring in vitro antigen production.

IL-33 protects from recurrent C. difficile infection by restoration of humoral immunity.

Clostridioides difficile infection (CDI) recurs in one of five patients. Monoclonal antibodies targeting the virulence factor TcdB reduce disease recurrence, suggesting that an inadequate anti-TcdB response to CDI leads to recurrence. In patients with CDI, we discovered that IL-33 measured at diagnosis predicts future recurrence, leading us to test the role of IL-33 signaling in the induction of humoral immunity during CDI. Using a mouse recurrence model, IL-33 was demonstrated to be integral for anti-TcdB antibody production. IL-33 acted via ST2+ ILC2 cells, facilitating germinal center T follicular helper (GC-Tfh) cell generation of antibodies. IL-33 protection from reinfection was antibody-dependent, as μMT KO mice and mice treated with anti-CD20 mAb were not protected. These findings demonstrate the critical role of IL-33 in generating humoral immunity to prevent recurrent CDI.

A self-amplifying RNA RSV prefusion-F vaccine elicits potent immunity in pre-exposed and naïve non-human primates

Newly approved subunit and mRNA vaccines for respiratory syncytial virus (RSV) demonstrate effectiveness in preventing severe disease, with protection exceeding 80% primarily through the generation of antibodies. An alternative vaccine platform called self-amplifying RNA (saRNA) holds promise in eliciting humoral and cellular immune responses. We evaluate the immunogenicity of a lipid nanoparticle (LNP)-formulated saRNA vaccine called SMARRT.RSV.preF, encoding a stabilized form of the RSV fusion protein, in female mice and in non-human primates (NHPs) that are either RSV-naïve or previously infected. Intramuscular vaccination with SMARRT.RSV.preF vaccine induces RSV neutralizing antibodies and cellular responses in naïve mice and NHPs. Importantly, a single dose of the vaccine in RSV pre-exposed NHPs elicits a dose-dependent anamnestic humoral immune response comparable to a subunit RSV preF vaccine. Notably, SMARRT.RSV.preF immunization significantly increases polyfunctional RSV.F specific memory CD4+ and CD8+ T-cells compared to RSV.preF protein vaccine. Twenty-four hours post immunization with SMARRT.RSV.preF, there is a dose-dependent increase in the systemic levels of inflammatory and chemotactic cytokines associated with the type I interferon response in NHPs, which is not observed with the protein vaccine. We identify a cluster of analytes including IL-15, TNFα, CCL4, and CXCL10, whose levels are significantly correlated with each other after SMARRT.RSV.preF immunization. These findings suggest saRNA vaccines have the potential to be developed as a prophylactic RSV vaccine based on innate, cellular, and humoral immune profiles they elicit.

Prediction of antibody-antigen interaction based on backbone aware with invariant point attention.

Antibodies play a crucial role in disease treatment, leveraging their ability to selectively interact with the specific antigen. However, screening antibody gene sequences for target antigens via biological experiments is extremely time-consuming and labor-intensive. Several computational methods have been developed to predict antibody-antigen interaction while suffering from the lack of characterizing the underlying structure of the antibody. Beneficial from the recent breakthroughs in deep learning for antibody structure prediction, we propose a novel neural network architecture to predict antibody-antigen interaction. We first introduce AbAgIPA: an antibody structure prediction network to obtain the antibody backbone structure, where the structural features of antibodies and antigens are encoded into representation vectors according to the amino acid physicochemical features and Invariant Point Attention (IPA) computation methods. Finally, the antibody-antigen interaction is predicted by global max pooling, feature concatenation, and a fully connected layer. We evaluated our method on antigen diversity and antigen-specific antibody-antigen interaction datasets. Additionally, our model exhibits a commendable level of interpretability, essential for understanding underlying interaction mechanisms. Quantitative experimental results demonstrate that the new neural network architecture significantly outperforms the best sequence-based methods as well as the methods based on residue contact maps and graph convolution networks (GCNs). The source code is freely available on GitHub at https://github.com/gmthu66/AbAgIPA .

P-IgGen: a paired antibody generative language model.

A key challenge in antibody drug discovery is designing novel sequences that are free from developability issues-such as aggregation, polyspecificity, poor expression, or low solubility. Here, we present p-IgGen, a protein language model for paired heavy-light chain antibody generation. The model generates diverse, antibody-like sequences with pairing properties found in natural antibodies. We also create a finetuned version of p-IgGen that biases the model to generate antibodies with 3D biophysical properties that fall within distributions seen in clinical-stage therapeutic antibodies. The model and inference code are freely available at www.github.com/oxpig/p-IgGen. Cleaned training data are deposited at doi.org/10.5281/zenodo.13880874.

DDO-adjuvanted influenza A virus nucleoprotein mRNA vaccine induces robust humoral and cellular type 1 immune responses and protects mice from challenge.

A challenge in viral vaccine development is to produce vaccines that generate both neutralizing antibodies to prevent infection and cytotoxic CD8+ T-cells that target conserved viral proteins and can eliminate infected cells to control virus spread. mRNA vaccines offer an opportunity to design vaccines based on conserved CD8-targeting epitopes, but achieving robust antigen-specific CD8+ T-cells remains a challenge. Here we tested the viral-derived oligonucleotide DDO268 as an adjuvant in the context of a model influenza A virus (IAV) nucleoprotein (NP) mRNA vaccine in C57BL/6 mice. DDO268 safely induced local type I interferon (IFN) production, stimulated dendritic cells type 1 (DC1) activation and migration to the draining lymph nodes, and improved the generation of IgG2c antibodies and antigen-specific effector Th1 CD4+ and CD8+ T-cells (IFNγ+TNFα+IL2+) when co-packaged with NP mRNA. The DDO268 adjuvanted vaccine provided enhanced protection against lethal IAV challenge and reduced the antigen dose required to achieve this protection. These results highlight the potential of DDO268 as an effective mRNA vaccine adjuvant and show that an IAV NP mRNA/DDO268 vaccine is a promising approach for generating protective immunity against conserved IAV epitopes.

Discovery of Therapeutic Antibodies Targeting Complex Multi-Spanning Membrane Proteins.

Complex integral membrane proteins, which are embedded in the cell surface lipid bilayer by multiple transmembrane spanning polypeptides, encompass families of proteins that are important target classes for drug discovery. These protein families include G protein-coupled receptors, ion channels, transporters, enzymes, and adhesion molecules. The high specificity of monoclonal antibodies and the ability to engineer their properties offers a significant opportunity to selectively bind these target proteins, allowing direct modulation of pharmacology or enabling other mechanisms of action such as cell killing. Isolation of antibodies that bind these types of membrane proteins and exhibit the desired pharmacological function has, however, remained challenging due to technical issues in preparing membrane protein antigens suitable for enabling and driving antibody drug discovery strategies. In this article, we review progress and emerging themes in defining discovery strategies for a generation of antibodies that target these complex membrane protein antigens. We also comment on how this field may develop with the emerging implementation of computational techniques, artificial intelligence, and machine learning.