Interaction Of Antibodies Research Articles

Single-Molecule Kinetic Observation of Antibody Interactions with Growing Amyloid β Fibrils.

Understanding the dynamic assembly process of amyloid β (Aβ) during fibril formation is essential for developing effective therapeutic strategies against Alzheimer's disease. Here, we employed high-speed atomic force microscopy to observe the growth of Aβ fibrils at the single-molecule level, focusing specifically on their interaction with anti-Aβ antibodies. Our findings show that fibril growth consists of intermittent periods of elongation and pausing, which are dictated by the alternating addition of Aβ monomers to protofilaments. We highlight the distinctive interaction of antibody 4396C, which specifically binds to the fibril ends in the paused state, suggesting a unique mechanism to hinder fibril elongation. Through real-time visualization of fibril growth and antibody interactions combined with molecular simulation, this study provides a refined understanding of Aβ assembly during fibril formation and suggests novel strategies for Alzheimer's therapy aimed at inhibiting the fibril elongation.

Improved deep learning prediction of antigen–antibody interactions

Identifying antibodies that neutralize specific antigens is crucial for developing effective immunotherapies, but this task remains challenging for many target antigens. The rise of deep learning-based computational approaches presents a promising avenue to address this challenge. Here, we assess the performance of a deep learning approach through two benchmark tests aimed at predicting antibodies for the receptor-binding domain of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein. Three different strategies for constructing input sequence alignments are employed for predicting structural models of antigen-antibody complexes. In our initial testing set, which comprises known experimental structures, these strategies collectively yield a significant top-ranked prediction for 61% of cases and a success rate of 47%. Notably, one strategy that utilizes the sequences of known antigen binders outperforms the other two, achieving a precision of 90% in a subsequent test set of ~1,000 antibodies, balanced between true and control antibodies for the antigen, albeit with a lower recall of 25%. Our results underscore the potential of integrating deep learning methods with single B cell sequencing techniques to enhance the prediction accuracy of antigen-antibody interactions.

Mutated Adenovirus Attacks in West Bengal, India: Risk Evaluation of Multi-Country Outbreaks and Mitigation Strategies.

The human adenovirus (HAdV) is beginning to spread rapidly in children through human, surface and animal vectors. Around 12,000 cases were recognised in 2022 in West Bengal and a shocking number of cases arose throughout India and in other under-developed areas. This is going to be a big threat to public health since no vaccine, awareness or protocol policies were introduced. Early detection, immediate isolation and proper policy developments are the key factors in overcoming the situation. Therefore, we performed this rapid review and discussed probable mitigation strategies, updated research on vaccine development, and treatment strategies to control the outbreaks of mutated HAdV. This is a narrative review of publicly available information. Here, we extracted updated information and data using the terms HAdV outbreaks, mutations, species, risks and prevention from Google Scholar and PubMed. We considered relevant articles that have discussed prevention strategies, ongoing research, and antiviral drugs for managing HAdV outbreaks. Early detection from throat swabs, isolation and symptomatic treatments are required to minimise viral infections. A massive test needs to be performed to find the affected people. The cases should be immediately isolated. It is recommended to treat high-touch surfaces with heat- or bleach-containing cleaners to prevent the spread of infection. Oxygen support and many broad-spectrum antivirals have been used to treat HAdV. Several studies showed antibody neutralisation and interactions between the natural killer cell receptor KIR3DS1 and HLA-F in infected cells, indicating possible therapeutic options in the future. HAdV-4 and HAdV-7 vaccines have been limitedly approved for administration to military personnel. Isolation, certain safety measures, broad-spectrum antiviral drugs and further research on new vaccines could be useful to prevent this virus from producing a worldwide pandemic. Also, the authorities should ensure the proper therapeutic interventions and nursing care facilities for the infected children. Patient or public contribution was not relevant to our work.

Molecular recognition characteristics of co-assembled peptides on atomically flat graphite surfaces

Molecular recognition, involving the binding of two or more molecules, is widely found in multiple disciplines. It plays a crucial role in driving specific molecular functionalization or biological activities such as antigen–antibody interactions. Recently, the molecular recognition of single peptides self-assembly at interfaces has been widely investigated since their broad applications in biosensors and bioelectronics. However, the recognition characteristics of peptide-peptide co-assembly on solids has not been investigated yet, which provides a basis for potential multi-probes biosensing or structure-intermingled functionalized bioelectronic applications. Here, we explored the molecular recognition characteristics of co-assembled peptides on two-dimensional (2D) layered nanomaterials, specifically graphite. Our findings showed distinct surface characteristics of peptide co-assembly in comparison to the independent peptides self-assembly. Peptide co-assembly exhibited the nucleation and growth heterogeneities with reduced nucleation and growth rates, dominated by a diffusion-limited step as confirmed via carrying out the sequential-assembled experiments. Moreover, molecular dynamics simulation reveals a slowdown binding process of co-assembled peptides to graphite. Furthermore, the misattachment of one peptide to arrays of another types of peptide with distinct structural ordering orientations severely postponed peptide elongation. Therefore, our work provides valuable insight into the fundamental surface characteristics of two co-assembled peptides as they specifically recognize graphite surface via undergoing continuous surface behaviors from binding to diffusion until final ordering process. The formation of co-assembled peptide patterns on 2D layered nanomaterials incorporates multiple functions enabling to provide potential applications in intermingled peptide-based biosensing or bioelectronic nanodevices.

Supramolecular Bioconjugation Strategy for Antibody-Targeted Delivery of siRNA.

RNA interference is a widely used biological process by which double-stranded RNA induces sequence-specific gene silencing by targeting mRNA for degradation. However, the physicochemical properties of siRNAs make their delivery extremely challenging, thus limiting their bioavailability at the target site. In this context, we developed a versatile and selective siRNA delivery system of a trastuzumab-conjugated nanocarrier. These immunoconjugates consist of the assembly by electrostatic interactions of an oligonucleotide-modified antibody with a cationic micelle for the targeted delivery of siRNA in HER2-overexpressing cancer cells. Results show that, when associated with the corresponding siRNA at the appropriate N/P ratio, our supramolecular assembly was able to efficiently induce luciferase and PLK-1 gene silencing in a cell-selective manner in vitro.

Flow cytometric analysis of the interaction of monoclonal antibodies to various epitopes of the HSP70 molecule with intracellular and membrane-associated forms of this protein

Currently, a large amount of data has demonstrated that many types of tumor cells, in contrast to their non-transformed forms, are characterized by the translocation of intracellular heat shock proteins 70 kDa (HSP70) to the surface of the plasma membrane. This made it possible to classify HSP70 exposed on the cell surface as a tumor-associated antigen and was the basis for searching the opportunities for the practical use of this phenomenon in clinical oncology. A significant argument in favor of the prospects of such studies was the discovered ability of HSP70, present on the surface of target cells, to enhance the cytotoxic activity of NK cells. In this regard, the work of many research groups is devoted to developing approaches to increasing the level of membrane-associated HSP70 in tumor tissues. At the same time, given the presence of such proteins on the surface of many types of tumor cells, the use of monoclonal antibodies that interact with HSP70 molecules for antitumor therapy can be considered as one of the promising approaches. It is well known that antibody preparations that selectively interact with cancer cells can be used for targeted antitumor immunotherapy. Previously, we obtained a panel of six B cell hybridomas producing monoclonal antibodies to the inducible and constitutive forms of human HSP70, directed to various epitopes of this molecule. It is significant that three varieties of hybridomas produced antibodies with specificity for binding sites on the C-terminal domain of the HSP70 molecule, and the second trio of monoclonal antibodies were specific to epitopes on the N-terminal domain of HSP70, while almost all known commercial antibodies interact only with C-terminal fragments of HSP70. In this work, we conducted a comparative study of the binding of the obtained antibodies to these proteins localized in different types of cells, both in the intracellular space and on the cell surface.The results obtained allow us to consider the identified varieties of monoclonal antibodies that most effectively recognize surface HSP70 as a promising basis for the creation of new drugs for antitumor immunotherapy.

Red Fluorescent Copper Nanoclusters for Fluorescence, Smartphone, and Electrochemical Sensor Arrays to Detect the Monkeypox A29 Protein.

An Orthopox zoonotic viral infection called monkeypox (MPXV) is the leading infectious disease globally. MPXV can easily spread from human to human through direct and indirect sexual contact; therefore, accurate and early detection of MPXV is crucial for reducing mortality. Fluorescence-based materials have received significant attention in recent years for biomedical applications. In this study, we synthesized red-fluorescent copper nanoclusters (CuNCs) with a size of less than 10 nm, which was confirmed by high-resolution transmission electron microscopy (HR-TEM) and atomic force microscopy (Bio-AFM) analysis. The synthesized CuNCs had a high fluorescence nature and were utilized for the detection of the MPXV (A29P) by an antigen-antibody conjugation using fluorescence, smartphone colorimetric, and electrochemical sensing techniques. The antigen (A29P) and antibody (Ab A29) interaction mechanisms were studied by X-ray photoelectron spectroscopic (XPS) analysis. Furthermore, fluorescence and electrochemical sensing were performed in PBS with detection limits of 0.096 and 0.114 nM, respectively. For real-world applications, the prepared immunosensor array can detect A29P in spiked serum samples, and point-of-care (POC) analysis, a smartphone-integrated sensor array, was used to measure the RGB color changes. The results showed that synthesized CuNCs are potential materials for detecting A29P via fluorescence and smartphone colorimetric and electrochemical sensing techniques.

Photon upconversion immunoprobe based on resonance energy transfer for brain natriuretic peptide – A prognostic biomarker for heart failure

Brain Natriuretic Peptide (BNP) holds significant clinical importance as a biomarker for heart-related conditions aiding in diagnosis, prognosis and monitoring of heart failure, providing valuable insights for timely intercession and patient management. Photon upconversion nanomaterials exhibit captivating ability to convert low energy photons to high energy ones, enabling enhanced sensitivity in sensing application. In this perspective, we develop a new photon upconversion based immunosensor for the detection of a heart failure biomarker, Brain Natriuretic Peptide (BNP) by Resonance Energy Transfer (RET) between Polyacrylic acid capped Mn2+ ions doped NaYF4:Yb/Er Upconversion Nanoparticles (PAA@Mn-NaYF4:Yb/Er UCNPs) as the donor and gold nanostar (AuNS) as the acceptor. BNP antibody was conjugated on the surface of PAA@Mn-NaYF4:Yb/Er UCNPs. The immunosensor can produce strong turn on luminescence intensity in proportional to increasing BNP antigen concentration through specific antigen–antibody interactions. The proposed photon upconversion based immunosensor can achieve turn on behaviour in the linear range from 30 pg/mL to 303 pg/mL with a Limit of Detection (LOD) of 1.76 pg/mL. The immunosensor exhibited appreciable selective and sensitive response towards BNP.

Elucidating the causal nexus between antibody-mediated immunity and autoimmune diseases: Insights from bidirectional mendelian randomization, gene expression profiling, and drug sensitivity analysis

ObjectiveThis study aimed to elucidate the causal relationships between antibodies and autoimmune diseases using Mendelian randomization (MR). MethodsData on 46 antibodies were obtained from genome-wide association studies (GWAS). Autoimmune disease data were sourced from the FinnGen consortium and the IEU OpenGWAS project. Inverse-variance weighted (IVW) analysis was the primary method, supplemented by heterogeneity and sensitivity analyses. We also examined gene expression near significant SNPs and conducted drug sensitivity analyses. ResultsAntibodies and autoimmune diseases exhibit diverse interactions. Antibodies produced after Polyomavirus infection tend to increase the risk of several autoimmune diseases, while those following Human herpesvirus 6 infection generally reduce it. The impact of Helicobacter pylori infection varies, with different antibodies affecting autoimmune diseases in distinct ways. Overall, antibodies significantly influence the risk of developing autoimmune diseases, whereas autoimmune diseases have a lesser impact on antibody levels. Gene expression and drug sensitivity analyses identified multiple genes and drugs as potential treatment options for ankylosing spondylitis (AS), with the AIF1 gene being particularly promising. ConclusionsBidirectional MR analysis confirms complex causal relationships between various antibodies and autoimmune diseases, revealing intricate patterns of post-infection antibody interactions. Several drugs and genes, notably AIF1, show potential as candidates for AS treatment, offering new avenues for research. Further exploration of the underlying mechanisms is necessary.

Characterization of a Novel Monoclonal Antibody with High Affinity and Specificity against Aflatoxins: A Discovery from Rosetta Antibody-Ligand Computational Simulation.

Aflatoxin B1 (AFB1) accumulates in crops, where it poses a threat to human health. To detect AFB1, anti-AFB1 monoclonal antibodies have been developed and are widely used. While the sensitivity and specificity of these antibodies have been extensively studied, information regarding the atomic-level docking of AFB1 (and its derivatives) with these antibodies is limited. Such information is crucial for understanding the key interactions that are required for high affinity and specificity in aflatoxin binding. First, a 3D comparative model of anti-AFB1 antibody (Ab-4B5G6) was predicted from the sequence using RosettaAntibody. We then utilized RosettaLigand to dock AFB1 onto ten homology models, producing a total of 10,000 binding modes. Interestingly, the best-scoring mode predicted strong interactions involving four sites within the heavy chain: ALA33, ASN52, HIS95, and TRP99. Importantly, these strong binding interactions exclusively involve the variable domain of the heavy chain. The best-scoring mode with AFB1 was also obtained through AF multimer combined with RosettaLigand, and two interactions at TRP and HIS were consistent with those found by Rosetta antibody-ligand computational simulation. The role of tryptophan in π interactions in antibodies was confirmed through mutation experiments, and the resulting mutant (W99A) exhibited a >1000-fold reduction in binding affinity for AFB1 and analogs, indicating the effect of tryptophan on the stability of CDR-H3 region. Additionally, we evaluated the binding of two glycolic acid-derived molecular derivatives (with impaired hydrogen bonding potential), and these derivatives (AFB2-GA and AFG2-GA) demonstrated a very weak binding affinity for Ab-4B5G6. The heavy chain was successfully isolated, and its sensitivity and specificity were consistent with those of the intact antibody. The homology models of variable heavy (VH) single-domain antibodies were established by RosettaAntibody, and the docking analysis revealed the same residues, including Ala, His, and Trp. Compared to the potential binding mode of fragment variable (FV) region, the results from a model of VH indicated that there are seven models involved in hydrophobic interaction with TYR32, which is usually referred to as polar amino acid and has both hydrophobic and hydrophilic features depending on the circumstances. Our work encompasses the entire process of Rosetta antibody-ligand computational simulation, highlighting the significance of variable heavy domain structural design in enhancing molecular interactions.

Analysis of the diverse antigenic landscape of the malaria protein RH5 identifies a potent vaccine-induced human public antibody clonotype

The highly conserved and essential Plasmodium falciparum reticulocyte-binding protein homolog 5 (PfRH5) has emerged as the leading target for vaccines against the disease-causing blood stage of malaria. However, the features of the human vaccine-induced antibody response that confer highly potent inhibition of malaria parasite invasion into red blood cells are not well defined. Here, we characterize 236 human IgG monoclonal antibodies, derived from 15 donors, induced by the most advanced PfRH5 vaccine. We define the antigenic landscape of this molecule and establish that epitope specificity, antibody association rate, and intra-PfRH5 antibody interactions are key determinants of functional anti-parasitic potency. In addition, we identify a germline IgG gene combination that results in an exceptionally potent class of antibody and demonstrate its prophylactic potential to protect against P.falciparum parasite challenge invivo. This comprehensive dataset provides a framework to guide rational design of next-generation vaccines and prophylactic antibodies to protect against blood-stage malaria.

Interaction of antiphospholipid antibodies with endothelial cells in antiphospholipid syndrome.

Antiphospholipid syndrome (APS) is an autoimmune disease with arteriovenous thrombosis and recurrent miscarriages as the main clinical manifestations. Due to the complexity of its mechanisms and the diversity of its manifestations, its diagnosis and treatment remain challenging issues. Antiphospholipid antibodies (aPL) not only serve as crucial "biomarkers" in diagnosing APS but also act as the "culprits" of the disease. Endothelial cells (ECs), as one of the core target cells of aPL, bridge the gap between the molecular level of these antibodies and the tissue and organ level of pathological changes. A more in-depth exploration of the relationship between ECs and the pathogenesis of APS holds the potential for significant advancements in the precise diagnosis, classification, and therapy of APS. Many researchers have highlighted the vital involvement of ECs in APS and the underlying mechanisms governing their functionality. Through extensive in vitro and in vivo experiments, they have identified multiple aPL receptors on the EC membrane and various intracellular pathways. This article furnishes a comprehensive overview and summary of these receptors and signaling pathways, offering prospective targets for APS therapy.

Anti-EGFR immunoliposomes for cabazitaxel delivery: From formulation development to in vivo evaluation in prostate cancer xenograft model

Liposomes functionalized with monoclonal antibodies offer targeted therapy for cancer, boasting advantages like sustained drug release, enhanced stability, passive accumulation in tumors, and interaction with overexpressed receptors on cancer cells. This study aimed to develop and characterize anti-EGFR immunoliposomes loaded with cabazitaxel and assess their properties against prostate cancer in vitro and in vivo. Using a Box-Behnken design, a formulation with soy phosphatidylcholine, 10% cholesterol, and a 1:20 drug-lipid ratio yielded nanometric particle size, low polydispersity and high drug encapsulation. Immunoliposomes were conjugated with cetuximab through DSPE-PEG-Maleimide lipid anchor. Characterization confirmed intact antibody structure and interaction with EGFR receptor following conjugation. Cabazitaxel was dispersed within the liposomes in the amorphous state, confirmed by solid-state analyses. In vitro release studies showed slower cabazitaxel release from immunoliposomes. Immunoliposomes had enhanced cabazitaxel cytotoxicity in EGFR-overexpressing DU145 cells without affecting non-tumor L929 cells. Cetuximab played an important role to improve cellular uptake in a time-dependent fashion in EGFR-overexpressing prostate cancer cells. In vivo, immunoliposomes led to significant tumor regression, improved survival, and reduced weight loss in xenograft mice. While cabazitaxel induced leukopenia, consistent with clinical findings, histological analysis revealed no evident toxicity. In conclusion, the immunoliposomes displayed suitable physicochemical properties for cabazitaxel delivery, exhibited cytotoxicity against EGFR-expressing prostate cancer cells, with high cell uptake, and induced significant tumor regression in vivo, with manageable systemic toxicity.

Techniques for improving the specificity of sandwich enzyme-linked immunosorbent assay-based drug screening.

ELISA assays are commonly used for drug screening by racing laboratories but are known to suffer from limited specificity. Inaccurate ELISA screening results are typically produced by non-specific antibody interactions or by the retention of chromogenic material in the sample well due to sample degradation. While confirmation of drug positives can be achieved by mass spectrometry, the follow-up of inaccurate ELISA screening results represents an unnecessary cost in staff time and reagents. This is particularly true in the case of rhEPO screening using sandwich ELISA assays, where the confirmation method requires up to 3days to perform. While most racing laboratories purchase commercial ELISA kits, these products can be customised to provide increased specificity for enhanced screening of positive samples. The specificity of commercial sandwich ELISA kits can be improved by a variety of mechanisms including the addition of competing analyte specific antibodies, substitution of capture antibodies or by performing ELISA analysis with and without capture antibodies. Non-specific signals in difficult matrices such as canine urine can also be reduced by the addition of BSA solutions to the ELISA plate prior to the addition of samples.

Anti-Inflammation Effectiveness of Ginger (Kaemferia galanga l.) and Shallots (Allium ascalonicum l.) Extract Combination on Sprague-Dawley Male Rat

Inflammation can be caused by various stimuli which include physical injury, infection, heat and antigen antibody interactions. Ginger (Kaempferia galanga L.) and Shallots (Allium ascalonicum L.) are medicinal plants that are often used by Indonesians as an alternative to natural medicine and have been studied to have good anti-inflammatory properties because they contain quercetin. This study aims to determine the effective dose of the combination of Ginger ethanol extract and Shallots as anti-inflammatory with a smaller dose. This study was carried out using male rats in 5 treatment groups, consisting of negative control (CMC-Na 0.5 %), control positive (diclofenac Na tablets 0,1 mg/kg body weight rat), and 3 combination doses of Ginger extract: Shallots extract, dose combination I (3 mg/kg body weight Rat: 2 mg / kg body weight Rat), dose combination II (6 mg / kg body weight Rat : 1 mg/kg body weight Rat), and the dose combination III (6 mg/kg body weight Rat: 2 mg kg body weight Rat) using Carrageenan Method on Rat's Feet. The results of the anti-inflammatory activity test showed that all the dose combination treatment groups had anti-inflammatory. The dose combination III was significantly different from the negative control group and showed the most effective dose of combination. The formulated combination shows a synergistic effect between ginger and shallots as an anti-inflammatory. Average percentage (%) of edema inhibition combination III is 71,08 %.

Macrocarpal B blocks the binding between the phospholipase A2 receptor and its antibodies

The pathogenic role of anti-phospholipase A2 receptor (PLA2R) antibodies in primary membranous nephropathy (MN) has been well-established. This study aimed to identify potential small-molecule inhibitors against the PLA2R-antibody interaction, offering potential therapeutic benefits. A comprehensive screening of over 4000 small-molecule compounds was conducted by ELISA to assess their inhibitory effects on the binding between the immobilized full-length extracellular PLA2R and its antibodies. The affinity of anti-PLA2R IgG from MN patients and the inhibitory efficacy of each compound were evaluated via surface plasmon resonance (SPR). Human podocyte injuries were analyzed using CCK-8 assay, wound healing assay, western blot analysis, and immunofluorescence, after exposure to MN plasma +/- blocking compound. Fifteen compounds were identified as potential inhibitors, demonstrating inhibition rates >20 % for the PLA2R-antibody interaction. Anti-PLA2R IgG exhibited a consistent affinity among patients (KD = 10−8 M). Macrocarpal B emerged as the most potent inhibitor, reducing the antigen–antibody interaction by nearly 30 % in a dose-dependent manner, comparable to the performance of the 31-mer peptide from the CysR domain. Macrocarpal B bound to the immobilized PLA2R with an affinity of 1.47 × 10−6 M, while showing no binding to anti-PLA2R IgG. Human podocytes exposed to MN plasma showed decreased podocin expression, impaired migration function, and reduced cell viability. Macrocarpal B inhibited the binding of anti-PLA2R IgG to podocytes and reduced the cellular injuries.

Deep learning of antibody epitopes using positional permutation vectors

BackgroundThe accurate computational prediction of B cell epitopes can vastly reduce the cost and time required for identifying potential epitope candidates for the design of vaccines and immunodiagnostics. However, current computational tools for B cell epitope prediction perform poorly and are not fit-for-purpose, and there remains enormous room for improvement and the need for superior prediction strategies. ResultsHere we propose a novel approach that improves B cell epitope prediction by encoding epitopes as binary positional permutation vectors that represent the position and structural properties of the amino acids within a protein antigen sequence that interact with an antibody. This approach supersedes the traditional method of defining epitopes as scores per amino acid on a protein sequence, where each score reflects each amino acids predicted probability of partaking in a B cell epitope antibody interaction. In addition to defining epitopes as binary positional permutation vectors, the approach also uses the 3D macrostructure features of the unbound protein structures, and in turn uses these features to train another deep learning model on the corresponding antibody-bound protein 3D structures. This enables the algorithm to learn the key structural and physiochemical features of the unbound protein and embedded epitope that initiate the antibody binding process helping to eliminate “induced fit” biases in the training data. We demonstrate that the strategy predicts B cell epitopes with improved accuracy compared to the existing tools. Additionally, we show that this approach reliably identifies the majority of experimentally verified epitopes on the spike protein of SARS-CoV-2 not seen by the model during training and generalizes in a very robust manner on dissimilar data not seen by the model during training. ConclusionsWith the approach described herein, a primary protein sequence and a query positional permutation vector encoding a putative epitope is sufficient to predict B cell epitopes in a reliable manner, potentially advancing the use of computational prediction of B cell epitopes in biomedical research applications.

Mathematical analysis of intrahost spread and control of Dengue Virus: Unraveling the crucial role of antigenic immunity

Studying viral infections within the host is crucial for understanding healthy cell responses and immunity. This research employed a reaction-diffusion Caputo fractional order model and a modified homotopy perturbation method to explore how immune cell memory and mobility affect the dynamic interactions of cytotoxic T-lymphocyte cells (CTLs), B-cell antibodies, uninfected monocytes, infected monocytes, and Dengue Virus (DENV) particle concentration within the host. The model guaranteed a positive solution, with the existence and uniqueness of the solution assured by the Banach fixed point theorem and a general stability supported by the Hyers-Ulam theorem. Sensitivity analysis highlighted that the DENV invasion rate speeds the spread of infected cells, while simulation results and fractional order analysis revealed that cell-mediated memory from past exposure will enhance the activation of CTLs and B-cell antibodies to strengthen immunity against dengue virus.

Probing the expression and adhesion of glycans involved in Helicobacter pylori infection

Helicobacter pylori infects approximately half the human population and has an unusual infective niche of the human stomach. Helicobacter pylori is a major cause of gastritis and has been classified as a group 1 carcinogen by the WHO. Treatment involves triple or quadruple antibiotic therapy, but antibiotic resistance is becoming increasingly prevalent. Helicobacter pylori expresses certain blood group related antigens (Lewis system) as a part of its lipopolysaccharide (LPS), which is thought to assist in immune evasion. Additionally, H. pylori LPS participates in adhesion to host cells alongside several adhesion proteins. This study profiled the carbohydrates of H. pylori reference strains (SS1 and 26695) using monoclonal antibodies (mAbs) and lectins, identifying interactions between two carbohydrate-targeting mAbs and multiple lectins. Atomic force microscopy (AFM) scans were used to probe lectin and antibody interactions with the bacterial surfaces. The selected mAb and lectins displayed an increased adhesive force over the surface of the curved H. pylori rods. Furthermore, this study demonstrates the ability of anti-carbohydrate antibodies to reduce the adhesion of H. pylori 26695 to human gastric adenocarcinoma cells via AFM. Targeting bacterial carbohydrates to disrupt crucial adhesion and immune evasion mechanisms represents a promising strategy for combating H. pylori infection.

Gold nanoclusters – 2D MoS2 nano couple: An immunosensor for the fluorescence turn-on detection of heart failure Biomarker Brain Natriuretic Peptide (BNP)

In the context of elevated morbidity and mortality risk of heart failure (HF), the establishment of prompt and sensitive diagnosis of HF is vital. A nanostructured fluorescence immuno sensing probe was constructed out of noble metal nanoclusters / two-dimensional transition metal dichalcogenide nano couple to target brain natriuretic peptide (BNP) antigen, a potential multi-utility heart failure biomarker. The green fluorescence of BNP-specific monoclonal antibody-conjugated gold nanoclusters was pre-quenched by a MoS2 two-dimensional nanosheet, which is subsequently enhanced in the presence of BNP antigen via target-specific antigen–antibody interaction. The probe is free from interferences by other potentially interfering possible co-existing biomolecules and offers easy, low-cost linear detection of BNP in the concentration range 0 to 360.82 pg/mL.