Generation and characterization of cross neutralizing human monoclonal antibody against 4 serotypes of dengue virus without enhancing activity

Machine-learning-assisted high-throughput identification of potent and stable neutralizing antibodies against all four dengue virus serotypes

Several computational methods have been developed to identify neutralizing antibodies (NAbs) covering four dengue virus serotypes (DENV-1 to DENV-4); however, limitations of the dataset and the resulting performance remain. Here, we developed a new computational framework to predict potent and stable NAbs against DENV-1 to DENV-4 using only antibody (CDR-H3) and epitope sequences as input. Specifically, our proposed computational framework employed sequence-based ML and molecular dynamic simulation (MD) methods to achieve more accurate identification. First, we built a novel dataset (n = 1108) by compiling the interactions of CDR-H3 and epitope sequences with the half maximum inhibitory concentration (IC50) values, which represent neutralizing activities. Second, we achieved an accurately predictive ML model that showed high AUC values of 0.879 and 0.885 by tenfold cross-validation and independent tests, respectively. Finally, our computational framework could be applied to filter approximately 2.5 million unseen antibodies into two final candidates that showed strong and stable binding to all four serotypes. In addition, the most potent and stable candidate (1B3B9_V21) was evaluated for its development potential as a therapeutic agent by molecular docking and MD simulations. This study provides an antibody computational approach to facilitate the high-throughput identification of NAbs and accelerate the development of therapeutic antibodies.

Nicotiana benthamiana as a potential source for producing anti-dengue virus D54 neutralizing therapeutic antibody

Dengue virus (DENV), transmitted by mosquitoes, is classified into four serotypes (DENV1-4) and typically causes mild, self-limiting symptoms upon initial infection. However, secondary infection can lead to severe symptoms due to antibody-dependent enhancement (ADE). To address this, anti-DENV antibodies are being developed with the goal of neutralizing infection without ADE activity. Previous attempts using a 54_hG1 antibody from CHO-K1 mammalian cells resulted in ADE induction, increasing viral infection. This study aimed to express the D54 monoclonal antibody in Nicotiana benthamiana. The plant-produced antibody had a similar neutralizing profile to the previous 54_hG1 antibody. Notably, the ADE activities of the plant-derived antibody were successfully eliminated, with no sign of viral induction. These findings suggest that N. benthamiana could be a source of therapeutic DENV antibodies. The method offers several advantages, including lower ADE, cost-effectiveness, simple facility requirements, scalability, and potential industrial-scale production in GMP facilities.

The dengue-specific immune response and antibody identification with machine learning

Dengue virus poses a serious threat to global health and there is no specific therapeutic for it. Broadly neutralizing antibodies recognizing all serotypes may be an effective treatment. High-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) and bioinformatic analysis enable in-depth understanding of the B-cell immune response. Here, we investigate the dengue antibody response with these technologies and apply machine learning to identify rare and underrepresented broadly neutralizing antibody sequences. Dengue immunization elicited the following signatures on the antibody repertoire: (i) an increase of CDR3 and germline gene diversity; (ii) a change in the antibody repertoire architecture by eliciting power-law network distributions and CDR3 enrichment in polar amino acids; (iii) an increase in the expression of JNK/Fos transcription factors and ribosomal proteins. Furthermore, we demonstrate the applicability of computational methods and machine learning to AIRR-seq datasets for neutralizing antibody candidate sequence identification. Antibody expression and functional assays have validated the obtained results.

Dengue virus neutralizing antibody: a review of targets, cross-reactivity, and antibody-dependent enhancement

Dengue is the most common viral infection spread by mosquitoes, prevalent in tropical countries. The acute dengue virus (DENV) infection is a benign and primarily febrile illness. However, secondary infection with alternative serotypes can worsen the condition, leading to severe and potentially fatal dengue. The antibody raised by the vaccine or the primary infections are frequently cross-reactive; however, weakly neutralizing, and during subsequent infection, they may increase the odds of antibody-dependent enhancement (ADE). Despite that, many neutralizing antibodies have been identified against the DENV, which are thought to be useful in reducing dengue severity. Indeed, an antibody must be free from ADE for therapeutic application, as it is pretty common in dengue infection and escalates disease severity. Therefore, this review has described the critical characteristics of DENV and the potential immune targets in general. The primary emphasis is given to the envelope protein of DENV, where potential epitopes targeted for generating serotype-specific and cross-reactive antibodies have critically been described. In addition, a novel class of highly neutralizing antibodies targeted to the quaternary structure, similar to viral particles, has also been described. Lastly, we have discussed different aspects of the pathogenesis and ADE, which would provide significant insights into developing safe and effective antibody therapeutics and equivalent protein subunit vaccines.

Retrospective investigation of the origin and epidemiology of the dengue outbreak in Yunnan, China from 2017 to 2018

Since 2013, a dengue epidemic has broken out in Yunnan, China and neighboring countries. However, after the COVID-19 pandemic in 2019, the number of dengue cases decreased significantly. In this retrospective study, epidemiological and genetic diversity characterizations of dengue viruses (DENV) isolated in Yunnan between 2017 and 2018 were performed. The results showed that the dengue outbreak in Yunnan from 2017 to 2018 was mainly caused by DENV1 (genotype I and genotype V) and DENV2 (Asia I, Asia II, and Cosmopolitan). Furthermore, correlation analysis indicated a significant positive correlation between the number of imported and local cases (correlation coefficient = 0.936). Multiple sequence alignment and phylogenetic divergence analysis revealed that the local isolates are closely related to the isolates from Myanmar and Laos. Interestingly, recombination analysis found that the DENV1 and DENV2 isolates in this study had widespread intra-serotype recombination. Taken together, the results of the epidemiological investigation imply that the dengue outbreak in Yunnan was primarily due to imported cases. This study provides a new reference for further investigations on the prevalence and molecular epidemiology of DENV in Yunnan, China.

Flavivirus Entry Inhibitors

Flaviviruses, including Dengue virus, Zika virus, Yellow fever virus, Japanese encephalitis virus, West Nile virus, cause thousands of deaths and millions of illnesses each year. The large outbreak of ZIKV in 2016 reminds us that flaviviruses can pose a serious threat to human safety and public health as emerging and re-emerging viruses. However, there are no specific drugs approved for the treatment of flavivirus infections. Due to no need to enter the cells, viral entry inhibitors have the unique advantage in suppressing viral infections. Flaviviruses bind to receptors and attach to the cell surface, then enter the endosome in a clathrin-dependent manner and finalizes the viral entry process after fusion with the cell membrane in a low pH environment. Small molecules, antibodies or peptides can inhibit flavivirus entry by targeting the above processes. Here, we focus on flavivirus entry inhibitors with well-defined target and antiviral activity. We hope that our review will provide a theoretical basis for flavivirus treatment and drug research and help to accelerate the clinical application of flavivirus entry inhibitors.

Discovery of B-cell epitopes for development of dengue vaccines and antibody therapeutics

Dengue is one of the most frequently transmitted viral infections globally which creates a serious burden to the healthcare system in many countries in the tropical and subtropical regions. To date, no vaccine has demonstrated balanced protection against the four dengue serotypes. Dengvaxia as the only vaccine that has been licensed for use in endemic areas has shown an increased risk in dengue-naïve vaccines to develop severe dengue. A crucial element in protection from dengue infection is the neutralizing antibody responses. Therefore, the identification of protective linear B-cell epitopes can guide vaccine design and facilitate the development of monoclonal antibodies as dengue therapeutics. This review summarizes the identification of dengue B-cell epitopes within the envelope (E) protein of dengue that can be incorporated into peptide vaccine constructs. These epitopes have been identified through approaches such as bioinformatics, three-dimensional structure analysis of antibody-dengue complexes, mutagenesis/alanine scanning and escape mutant studies. Additionally, the therapeutic potential of monoclonal antibodies targeting the E protein of dengue is reviewed. This can provide a basis for the design of future dengue therapies.

Stress-dependent flexibility of a full-length human monoclonal antibody: Insights from molecular dynamics to support biopharmaceutical development

After several decades of advancements in drug discovery, product development of biopharmaceuticals remains a time- and resource-consuming endeavor. One of the main reasons is associated to the lack of fundamental understanding of conformational dynamics of such biologic entities, and how they respond to various stresses encountered during manufacturing. In this work, we have studied the conformational dynamics of human IgG₁κ b12 monoclonal antibody (mAb) using molecular dynamics simulations. The hundreds of nanoseconds long trajectories reveal that b12 mAb is highly flexible. Its variable domains show greater conformational fluctuations than the constant domains. Additionally, it collapses towards a more globular shape in response to thermal stress, leading to decrease in the total solvent exposed surface area and radius of gyration. This behavior is more pronounced for the deglycosylated b12 mAb, and it appears to correlate with increase in inter-domain contacts between specific regions of the antibody. Conformational fluctuations also cause temporary formation and disruption of hydrophobic and charged patches on the antibody surface, which is particularly important for the prediction of CMC properties during development phases of antibody-based biotherapeutics. The insights gained through these simulations may help the development of biologic drugs, especially with regards to manufacturing processes where antibodies may undergo significant thermal stress.

Machine Learning Detects Anti-DENV Signatures in Antibody Repertoire Sequences

Dengue infection is a global threat. As of today, there is no universal dengue fever treatment or vaccines unreservedly recommended by the World Health Organization. The investigation of the specific immune response to dengue virus would support antibody discovery as therapeutics for passive immunization and vaccine design. High-throughput sequencing enables the identification of the multitude of antibodies elicited in response to dengue infection at the sequence level. Artificial intelligence can mine the complex data generated and has the potential to uncover patterns in entire antibody repertoires and detect signatures distinctive of single virus-binding antibodies. However, these machine learning have not been harnessed to determine the immune response to dengue virus. In order to enable the application of machine learning, we have benchmarked existing methods for encoding biological and chemical knowledge as inputs and have investigated novel encoding techniques. We have applied different machine learning methods such as neural networks, random forests, and support vector machines and have investigated the parameter space to determine best performing algorithms for the detection and prediction of antibody patterns at the repertoire and antibody sequence levels in dengue-infected individuals. Our results show that immune response signatures to dengue are detectable both at the antibody repertoire and at the antibody sequence levels. By combining machine learning with phylogenies and network analysis, we generated novel sequences that present dengue-binding specific signatures. These results might aid further antibody discovery and support vaccine design.

Monoclonal Antibodies Against Infectious Microbes: So Long and Too Little!

Monoclonal antibodies (mAbs) as alternatives or more often as complementary to the conventional antimicrobials have been developed for the management of infectious conditions for the past two decades. These pharmacotherapeutic strategies are inevitable as the burden of antimicrobial resistance is far-reaching in recent times. MAbs are part of the targeted pharmacotherapy armamentarium with a high degree of specificity - hence, exert comparatively superior efficacy and tolerability than the conventional polyclonal antisera. So far, only five mAbs have been approved for the management of infectious states, since the marketing authorization (1998) given to palivizumab (Synagis®) for the prophylaxis of lower respiratory tract disease caused by a respiratory syncytial virus in pediatric patients. Ibalizumab-uiyk (Trogarzo™) used for the management of multidrug-resistant HIV-1 infection not yielding to at least 10 antiretroviral drugs, was approved recently. Among the three antibacterial mAbs, raxibacumab (ABthrax®/ Anthrin®) and obiltoxaximab (Anthim®) are indicated for the treatment and prophylaxis of inhalation anthrax due to Bacillus anthracis; bezlotoxumab (Zinplava®) is used to reduce the recurrence of Clostridium difficile infection. There are also around 30 and 15 mAbs in different phases of development for viral and bacterial conditions. As alternatives to the traditional antivirals and antibacterials, the antimicrobial mAbs are the need of the hour. These mAbs are more relevant to the management of conditions like emerging viral outbreaks wherein there is a lack of prophylactic vaccines. The current cutting-edge engineering technologies revolutionizing the production of mAbs include phagedisplayed antibody libraries, cloning from single-memory B cells or single-antibody-secreting plasma B cells, proteomics-directed cloning of mAbs from serum clubbed with high-throughput sequencing techniques. Yet, the cost of manufacture continues to be the main limiting factor. In this review, the different therapeutic monoclonal antibodies directed against the microbial pathogens are discussed.

Prospective Artificial Intelligence to Dissect the Dengue Immune Response and Discover Therapeutics

Dengue virus (DENV) poses a serious threat to global health as the causative agent of dengue fever. The virus is endemic in more than 128 countries resulting in approximately 390 million infection cases each year. Currently, there is no approved therapeutic for treatment nor a fully efficacious vaccine. The development of therapeutics is confounded and hampered by the complexity of the immune response to DENV, in particular to sequential infection with different DENV serotypes (DENV1-5). Researchers have shown that the DENV envelope (E) antigen is primarily responsible for the interaction and subsequent invasion of host cells for all serotypes and can elicit neutralizing antibodies in humans. The advent of high-throughput sequencing and the rapid advancements in computational analysis of complex data, has provided tools for the deconvolution of the DENV immune response. Several types of complex statistical analyses, machine learning models and complex visualizations can be applied to begin answering questions about the B- and T-cell immune responses to multiple infections, antibody-dependent enhancement, identification of novel therapeutics and advance vaccine research.

Understanding the role of antibody glycosylation through the lens of severe viral and bacterial diseases

Abundant evidence points to a critical role for antibodies in protection and pathology across infectious diseases. While the antibody variable domain facilitates antibody binding and the blockade of infection, the constant domain (Fc) mediates cross talk with the innate immune system. The biological activity of the Fc region is controlled genetically via class switch recombination, resulting in the selection of distinct antibody isotypes and subclasses. However, a second modification is made to all antibodies, via post-translational changes in antibody glycosylation. Studies from autoimmunity and oncology have established the role of immunoglobulin G (IgG) Fc glycosylation as a key regulator of humoral immune activity. However, a growing body of literature, exploring IgG Fc glycosylation through the lens of infectious diseases, points to the role of inflammation in shaping Fc-glycan profiles, the remarkable immune plasticity in antibody glycosylation across pathogen-exposed populations, the canonical and noncanonical functions of glycans and the existence of antigen-specific control over antibody Fc glycosylation. Ultimately, this work provides critical new insights into the functional roles for antibody glycosylation as well as lays the foundation for leveraging antibody glycosylation to drive prevention or control across diseases.

Reassessing therapeutic antibodies for neglected and tropical diseases

In the past two decades there has been a significant expansion in the number of new therapeutic monoclonal antibodies (mAbs) that are approved by regulators. The discovery of these new medicines has been driven primarily by new approaches in inflammatory diseases and oncology, especially in immuno-oncology. Other recent successes have included new antibodies for use in viral diseases, including HIV. The perception of very high costs associated with mAbs has led to the assumption that they play no role in prophylaxis for diseases of poverty. However, improvements in antibody-expression yields and manufacturing processes indicate this is a cost-effective option for providing protection from many types of infection that should be revisited. Recent technology developments also indicate that several months of protection could be achieved with a single dose. Moreover, new methods in B cell sorting now enable the systematic identification of high-quality antibodies from humanized mice, or patients. This Review discusses the potential for passive immunization against schistosomiasis, fungal infections, dengue, and other neglected diseases.