Antibody Binding Sites Research Articles

Association of human leucocyte antigen loci with vaccine-induced immune thrombotic thrombocytopenia: Potential role of the interaction between platelet factor 4-derived peptides and MHC-II.

No risk factors have been identified for vaccine-induced immune thrombotic thrombocytopenia (VITT) so far. The aim of this study was to identify human leucocyte antigen (HLA) alleles potentially associated with VITT susceptibility. Specific HLA class II alleles were detected with significantly higher frequency in VITT patients compared with Italian controls: DPB1*17:01, DQA1*05:01, and DRB1*11:04. In silico analysis revealed increased affinity of DRB1*11:04 for a platelet factor 4 (PF4)-derived peptide, ITSLEVIKA, that contains two amino acids present in the specific binding site of anti-PF4 antibodies from VITT patients. Our findings show for the first time a genetic predisposition to developing anti-PF4 antibodies in response to Ad-vector vaccines.

One N-glycan regulates natural killer cell antibody-dependent cell-mediated cytotoxicity and modulates Fc γ receptor IIIa/CD16a structure.

Both endogenous antibodies and a subset of antibody therapeutics engage Fc gamma receptor (FcγR)IIIa/CD16a to stimulate a protective immune response. Increasing the FcγRIIIa/IgG1 interaction improves the immune response and thus represents a strategy to improve therapeutic efficacy. FcγRIIIa is a heavily glycosylated receptor and glycan composition affects antibody-binding affinity. Though our laboratory previously demonstrated that natural killer (NK) cell N-glycan composition affected the potency of one key protective mechanism, antibody-dependent cell-mediated cytotoxicity (ADCC), it was unclear if this effect was due to FcγRIIIa glycosylation. Furthermore, the structural mechanism linking glycan composition to affinity and cellular activation remained undescribed. To define the role of individual amino acid and N-glycan residues, we measured affinity using multiple FcγRIIIa glycoforms. We observed stepwise affinity increases with each glycan truncation step, with the most severely truncated glycoform displaying the highest affinity. Removing the N162 glycan demonstrated its predominant role in regulating antibody-binding affinity, in contrast to four other FcγRIIIa N-glycans. We next evaluated the impact of the N162 glycan on NK cell ADCC. NK cells expressing the FcγRIIIa V158 allotype exhibited increased ADCC following kifunensine treatment to limit N-glycan processing. Notably, an increase was not observed with cells expressing the FcγRIIIa V158 S164A variant that lacks N162 glycosylation, indicating that the N162 glycan is required for increased NK cell ADCC. To gain structural insight into the mechanisms of N162 regulation, we applied a novel protein isotope labeling approach in combination with solution NMR spectroscopy. FG loop residues proximal to the N162 glycosylation site showed large chemical shift perturbations following glycan truncation. These data support a model for the regulation of FcγRIIIa affinity and NK cell ADCC whereby composition of the N162 glycan stabilizes the FG loop and thus the antibody-binding site.

One N-glycan regulates natural killer cell antibody-dependent cell-mediated cytotoxicity and modulates Fc γ receptor IIIa/CD16a structure

Both endogenous antibodies and a subset of antibody therapeutics engage Fc gamma receptor (FcγR)IIIa/CD16a to stimulate a protective immune response. Increasing the FcγRIIIa/IgG1 interaction improves the immune response and thus represents a strategy to improve therapeutic efficacy. FcγRIIIa is a heavily glycosylated receptor and glycan composition affects antibody-binding affinity. Though our laboratory previously demonstrated that natural killer (NK) cell N-glycan composition affected the potency of one key protective mechanism, antibody-dependent cell-mediated cytotoxicity (ADCC), it was unclear if this effect was due to FcγRIIIa glycosylation. Furthermore, the structural mechanism linking glycan composition to affinity and cellular activation remained undescribed. To define the role of individual amino acid and N-glycan residues, we measured affinity using multiple FcγRIIIa glycoforms. We observed stepwise affinity increases with each glycan truncation step, with the most severely truncated glycoform displaying the highest affinity. Removing the N162 glycan demonstrated its predominant role in regulating antibody-binding affinity, in contrast to four other FcγRIIIa N-glycans. We next evaluated the impact of the N162 glycan on NK cell ADCC. NK cells expressing the FcγRIIIa V158 allotype exhibited increased ADCC following kifunensine treatment to limit N-glycan processing. Notably, an increase was not observed with cells expressing the FcγRIIIa V158 S164A variant that lacks N162 glycosylation, indicating that the N162 glycan is required for increased NK cell ADCC. To gain structural insight into the mechanisms of N162 regulation, we applied a novel protein isotope labeling approach in combination with solution NMR spectroscopy. FG loop residues proximal to the N162 glycosylation site showed large chemical shift perturbations following glycan truncation. These data support a model for the regulation of FcγRIIIa affinity and NK cell ADCC whereby composition of the N162 glycan stabilizes the FG loop and thus the antibody-binding site.

Genetic characteristics of human parainfluenza viruses 1-4 associated with acute lower respiratory tract infection in Chinese children, during 2015-2021.

Human parainfluenza viruses (HPIVs) are a significant cause of acute lower respiratory tract infections (ALRTIs) among young children and elderly individuals worldwide. The four types of HPIVs (HPIV1-4) can cause recurrent infections and pose a significant economic burden on health care systems globally. However, owing to the limited availability of complete genome sequences, the genetic evolution of these viruses and the development of vaccines and antiviral treatments are hampered. To address this issue, this study utilized next-generation sequencing to obtain 156 complete genome sequences of HPIV1-4, which were isolated from hospitalized children with ALRTIs in six regions of China between 2015 and 2021. This study revealed multiple clades, lineages, or sublineages of HPIVs circulating in mainland China, with a novel clade D of HPIV1 identified as geographically restricted to China. Moreover, this study identified the endemic dominant genotype of HPIV3, lineage C3, which has widely spread and continuously circulated in China. Bioinformatic analysis of the genome sequences revealed that the proteins of HPIV3 possessed the most variable sites, with the P protein showing more diversity than the other proteins among all types of HPIVs. The HN proteins of HPIV1-3 are all under negative/purifying selection, and two amino acid substitutions in the HN proteins correspond to known mAb neutralizing sites in the two HPIV3 strains. These findings provide crucial insights into the genetic diversity and evolutionary dynamics of HPIVs circulating among children in China and may facilitate research on the molecular diagnosis, vaccine development, and surveillance of HPIVs.IMPORTANCEPhylogenetic analysis revealed the prevalence of multiple clades, lineages, or sublineages of human parainfluenza viruses (HPIVs) circulating in mainland China. Notably, a unique evolutionary branch of HPIV1 containing only Chinese strains was identified and designated clade D. Furthermore, in 2023, HPIV3 strains from Pakistan and Russia formed a new lineage within clade C, named C6. The first HPIV4b sequence obtained in this study from China belongs to lineage C2. Evolutionary rate assessments revealed that both the HN and whole-genome sequences of HPIV3 presented the lowest evolutionary rates compared with those of the other HPIV types, with rates of 6.98E-04 substitutions/site/year (95% HPD: 5.87E-04 to 8.25E-03) and 5.85E-04 substitutions/site/year (95% HPD: 5.12E-04 to 6.62E-04), respectively. Recombination analysis revealed a potential recombination event in the F gene of an HPIV1 strain in this study. Additionally, all the newly obtained HPIV1-3 strains exhibited negative selection pressure, and two mutations were identified in the HN protein of two HPIV3 strains at monoclonal antibody-binding sites.

Chagas Disease Diagnosis with Trypanosoma cruzi-Exclusive Epitopes in GFP.

Serological tests are critical tools in the fight against infectious disease. They detect antibodies produced during an adaptive immune response against a pathogen with an immunological reagent, whose antibody binding characteristics define the specificity and sensitivity of the assay. While pathogen proteins have conveniently served as reagents, their performance is limited by the natural grouping of specific and non-specific antibody binding sites, epitopes. An attractive solution is to build synthetic proteins that only contains pathogen-specific epitopes, which could theoretically reach 100% specificity. However, the genesis of de novo proteins remains a challenge. To address the uncertainty of producing a synthetic protein, we have repurposed the beta barrel of fluorescent proteins into a receptacle that can receive several epitope sequences without compromising its ability to be expressed. Here, two versions of a multiepitope protein were built using the receptacle that differ by their grouping of epitopes specific to the parasite Trypanosoma cruzi, the causative agent for Chagas disease. An evaluation of their performance as the capture reagent in ELISAs showed near-complete agreement with recommended diagnostic protocols. The results suggest that a single assay could be developed for the diagnosis of Chagas disease and that this approach could be applied to other diseases.

The asymmetric opening of HIV-1 Env by a potent CD4 mimetic enables anti-coreceptor binding site antibodies to mediate ADCC.

HIV-1 envelope glycoproteins (Env) from primary HIV-1 isolates typically adopt a pretriggered "closed" conformation that resists to CD4-induced (CD4i) non-neutralizing antibodies (nnAbs) mediating antibody-dependent cellular cytotoxicity (ADCC). CD4-mimetic compounds (CD4mcs) "open-up" Env allowing binding of CD4i nnAbs, thereby sensitizing HIV-1-infected cells to ADCC. Two families of CD4i nnAbs, the anti-cluster A and anti-coreceptor binding site (CoRBS) Abs, are required to mediate ADCC in combination with the indane CD4mc BNM-III-170. Recently, new indoline CD4mcs with improved potency and breadth have been described. Here, we show that the lead indoline CD4mc, CJF-III-288, sensitizes HIV-1-infected cells to ADCC mediated by anti-CoRBS Abs alone, contributing to improved ADCC activity. Structural and conformational analyses reveal that CJF-III-288, in combination with anti-CoRBS Abs, potently stabilizes an asymmetric "open" State-3 Env conformation, This Env conformation orients the anti-CoRBS Ab to improve ADCC activity and therapeutic potential.

One N-glycan regulates natural killer cell antibody-dependent cell-mediated cytotoxicity and modulates Fc γ receptor IIIa / CD16a structure.

Both endogenous antibodies and a subset of antibody therapeutics engage Fc gamma receptor (FcγR)IIIa / CD16a to stimulate a protective immune response. Increasing the FcγRIIIa/IgG1 interaction improves the immune response and thus represents a strategy to improve therapeutic efficacy. FcγRIIIa is a heavily glycosylated receptor and glycan composition affects antibody-binding affinity. Though our laboratory previously demonstrated that natural killer (NK) cell N-glycan composition affected the potency of one key protective mechanism, antibody-dependent cell-mediated cytotoxicity (ADCC), it was unclear if this effect was due to FcγRIIIa glycosylation. Furthermore, the structural mechanism linking glycan composition to affinity and cellular activation remained undescribed. To define the role of individual amino acid and N-glycan residues we measured affinity using multiple FcγRIIIa glycoforms. We observed stepwise affinity increases with each glycan truncation step with the most severely truncated glycoform displaying the highest affinity. Removing the N162 glycan demonstrated its predominant role in regulating antibody-binding affinity, in contrast to four other FcγRIIIa N-glycans. We next evaluated the impact of the N162 glycan on NK cell ADCC. NK cells expressing the FcγRIIIa V158 allotype exhibited increased ADCC following kifunensine treatment to limit N-glycan processing. Notably, an increase was not observed with cells expressing the FcγRIIIa V158 S164A variant that lacks N162 glycosylation, indicating the N162 glycan is required for increased NK cell ADCC. To gain structural insight into the mechanisms of N162 regulation, we applied a novel protein isotope labeling approach in combination with solution NMR spectroscopy. FG loop residues proximal to the N162 glycosylation site showed large chemical shift perturbations following glycan truncation. These data support a model for the regulation of FcγRIIIa affinity and NK cell ADCC whereby composition of the N162 glycan stabilizes the FG loop and thus the antibody-binding site.

Living in LALA land? Forty years of attenuating Fc effector functions.

The Fc region of antibodies is vital for most of their physiological functions, many of which are engaged through binding to a range of Fc receptors. However, these same interactions are not always helpful or wanted when therapeutic antibodies are directed against self-antigens, and can sometimes cause catastrophic adverse reactions. Over the past 40 years, there have been intensive efforts to "silence" unwanted binding to Fc-gamma receptors, resulting in at least 45 different variants which have entered clinical trials. One of the best known is "LALA" (L234A/L235A). However, neither this, nor most of the other variants in clinical use are completely silenced, and in addition, the biophysical properties of many of them are compromised. I review the development of different variants to see what we can learn from their biological properties and use in the clinic. With the rise of powerful new uses of antibody therapy such as bispecific T-cell engagers, antibody-drug conjugates, and checkpoint inhibitors, it is increasingly important to optimize the Fc region as well as the antibody binding site in order to achieve the best combination of safety and efficacy.

Si Nanorod Array Integrated Microfluidic Device for Enhanced Extracellular Vesicle Isolation

AbstractTumor‐derived extracellular vesicles (EVs) have attracted tremendous interest as one of the early cancer diagnostic markers. The major obstacle preventing EV‐based liquid biopsy is the efficient collection of EVs from the complex body fluid environment. This paper introduces a nanorod‐integrated microfluidic chip capable of immunoaffinity‐isolating EVs. Periodic silicon nanorod arrays in zigzag channels are prepared by nanosphere lithography. Nanorod sidewalls provide larger binding sites for antibodies, and their close interspacing to the EV sizes improves the binding probability. The fluid simulation results show that the significant increase in isolation efficiency also comes from the liquid perturbation enhanced by the particular nanorod arrangement. Under optimal operating conditions, plasma samples from patients (n = 14) with different types of cancers (hepatocellular carcinoma, colorectal cancer, and pancreatic adenocarcinoma) to the chip for EV isolation is applied. In this proof‐of‐concept study, the expression level of the epidermal growth factor receptor (EGFR) in isolated EVs is then quantified using droplet digital PCR, showing good diagnostic performance in cancer detection.

Geometric epitope and paratope prediction.

Identifying the binding sites of antibodies is essential for developing vaccines and synthetic antibodies. In this article, we investigate the optimal representation for predicting the binding sites in the two molecules and emphasize the importance of geometric information. Specifically, we compare different geometric deep learning methods applied to proteins' inner (I-GEP) and outer (O-GEP) structures. We incorporate 3D coordinates and spectral geometric descriptors as input features to fully leverage the geometric information. Our research suggests that different geometrical representation information is useful for different tasks. Surface-based models are more efficient in predicting the binding of the epitope, while graph models are better in paratope prediction, both achieving significant performance improvements. Moreover, we analyze the impact of structural changes in antibodies and antigens resulting from conformational rearrangements or reconstruction errors. Through this investigation, we showcase the robustness of geometric deep learning methods and spectral geometric descriptors to such perturbations. The python code for the models, together with the data and the processing pipeline, is open-source and available at https://github.com/Marco-Peg/GEP.

Determination of the cervical cancer biomarker SCCA using CMK-3@UiO-66@AuNPs composite-modified glassy carbon electrodes

In order to detect the cervical cancer biomarker squamous cell carcinoma antigen (SCCA) in human serum, an electrochemical immunosensor was constructed. Zirconium 1,4-dicarboxybenzene MOF (UiO-66), with a high specific surface area, was coupled with gold nanoparticles (AuNPs), creating the UiO-66@AuNPs nanomaterial. This coupling increased the sensitivity of the electrochemical immunosensor by providing many biological binding sites for antibodies to bind to Au-S bonds. Then, mesoporous carbon (CMK-3) was added to the UiO-66@AuNPs nanomaterial to obtain a CMK-3@UiO-66@AuNPs nanocomposite. This further increased the electron transfer proficiency of the material and enhanced the electrochemical signal. Finally, the sensitive detection of squamous cell carcinoma antigen (SCCA) was made possible by unique immunological responses between antigens and antibodies. Transmission electron microscopy (TEM) analysis of CMK-3@UiO-66@AuNPs revealed embedded surfaces and voids; cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) confirmed the successful assembly of the electrochemical immunosensor. The developed electrochemical immunosensor demonstrated good linearity (R12 = 0.999) from 0.01 pg/mL to 10,000 pg/mL, which is the concentration range of SCCA in human serum. The limit of detection was 0.0034 pg/mL (at an S/N ratio of 3). The immunosensor exhibited excellent precision, stability and selectivity, with a high rate of recovery (98.26–101.8 %). The experimental validation studies demonstrated that the electrochemical immunosensor was effective for the detection of SCCA in human serum, offering a novel method for the early diagnosis and dynamic surveillance of cervical cancer.

Highly sensitive in-situ growth gold dendrite structure electrochemical sensor for early Alzheimer's disease screening

Beta-amyloid 42 (Aβ-42) peptide is an essential biomarker for Alzheimer's disease (AD) diagnosis. This study presents high sensitivity and stability sensors for Aβ-42 peptide detection, along with an integrated handheld analysis and display device. The sensors, with a wide response range and high accuracy, capable of measuring Aβ-42 peptide concentration at the femtogram level, could have enabled early screening for AD. Employing an in-situ grown three-dimensional sensor, the specific surface area of the sensor was increased by 200 % which, thereby, provided more antibody binding sites to enhance detection accuracy. This electrochemical sensor demonstrated a broad linear response range from 4.5 × 10−8 pg/mL to 4.5 × 102 pg/mL and could accurately determine the concentration of spiked analytes (including artificial saliva, human plasma, and human blood). Furthermore, the sensor exhibited satisfactory stability, with only a 5 % sensitivity loss after 35 days of storage at 4 °C. Additionally, this handheld Aβ-42 peptide testing device incorporates a display for result delivery. Such innovative technology could fill the gap in the market for portable testing instruments and could provide an efficient and reliable solution for early AD screening.

M6ACali: machine learning-powered calibration for accurate m6A detection in MeRIP-Seq.

We present m6ACali, a novel machine-learning framework aimed at enhancing the accuracy of N6-methyladenosine (m6A) epitranscriptome profiling by reducing the impact of non-specific antibody enrichment in MeRIP-Seq. The calibration model serves as a genomic feature-based classifier that refines the identification of m6A sites, distinguishing those genuinely present from those that can be detected in in-vitro transcribed (IVT) control experiments. We find that m6ACali effectively identifies non-specific binding peaks reported by exomePeak2 and MACS2 in novel MeRIP-Seq datasets without the need for paired IVT controls. The model interpretation revealed that off-target antibody binding sites commonly occur at short exons and short mRNAs, originating from high read coverage regions that share the motif sequence with true m6A sites. We also reveal that the ML strategy can efficiently adjust differentially methylated peaks and other antibody-dependent, base-resolution m6A detection techniques. As a result, m6ACali offers a promising method for the universal enhancement of m6A profiles generated by MeRIP-Seq experiments, elevating the benchmark for omics-level m6A data integration.

Structural analyses of the GI.4 norovirus by cryo-electron microscopy and X-ray crystallography revealing binding sites for human monoclonal antibodies.

We conducted the structural analyses of the VP1 protein from the GI.4 Chiba norovirus to identify the binding sites of the previously isolated human monoclonal antibodies CV-1A1 and CV-2F5. The cryo-electron microscopy of the Chiba virus-like particles (VLPs) complexed with the Fv-clasp forms of GI.4-specific CV-1A1 revealed that this antibody binds to the highly variable P2 subdomain, suggesting that this antibody may have neutralizing ability against the GI.4 strains. X-ray crystallography revealed that the CV-2F5 antibody bound to the P1 subdomain, which is rich in conserved amino acids. This result is consistent with the ability of the CV-2F5 antibody to react with a wide variety of GI norovirus strains. It is also found that the CV-2F5 antibody caused a disruption of VLPs. Our findings, together with previous reports on the structures of VP1 proteins and VLPs, are expected to open a path for the structure-based development of antivirals and vaccines against norovirus disease.

Immune-like sandwich multiple hotspots SERS biosensor for ultrasensitive detection of NDKA biomarker in serum

Developing the rapid, specific, and sensitive tumor marker NDKA biosensor has become an urgent need in the field of early diagnosis of colorectal cancer (CRC). Surface-enhanced Raman spectroscopy (SERS) with the advantages of high sensitivity, high resolution as well as providing sample fingerprint, enables rapid and sensitive detection of tumor markers. However, many SERS biosensors rely on boosting the quantity of Raman reporter molecules on individual nanoparticle surfaces, which can result in nanoparticle agglomeration, diminishing the stability and sensitivity of NDKA detection. Here, we proposed an immune-like sandwich multiple hotspots SERS biosensor for highly sensitive and stable analysis of NDKA in serum based on molecularly imprinted polymers and NDKA antibody. The SERS biosensor employs an array of gold nanoparticles, which are coated with a biocompatible polydopamine molecularly imprinted polymer as a substrate to specifically capture NDKA. Then the biosensor detects NDKA through Raman signals as a result of the specific binding of NDKA to the SERS nanotag affixed to the capture substrate along with the formation of multiple hotspots. This SERS biosensor not only avoids the aggregation of nanoparticles but also presents a solution to the obstacles encountered in immune strategies for certain proteins lacking multiple antibody or aptamer binding sites. Furthermore, the practical application of the SERS biosensor is validated by the detection of NDKA in serum with the lower limit of detection (LOD) of 0.25 pg/mL, meanwhile can detect NDKA of 10 ng/mL in mixed proteins solution, illustrating high sensitivity and specificity. This immune-like sandwich multiple hotspots biosensor makes it quite useful for the early detection of CRC and also provides new ideas for cancer biomarker sensing strategy in the future.

A sensitive immunosensor for the detection of alkaline phosphatase as a biomarker for fracture healing

Fractures occur at all ages and are highly prevalent. At the same time, there is a problem of delayed healing after fracture, and drugs are often taken to promote healing. Alkaline phosphatase (ALP) is an important indicator for assessing fracture healing, and achieving its quantification would be helpful in evaluating fracture recovery in patients on medication. Here, we present an ultrasensitive immunosensor based on NH2-MIL-101(Cr)@AuNPs/rGO nanocomposites. The poor conductivity of metal–organic skeletons (MOF) limits their electrochemical applications. In this study, NH2-MIL-101(Cr) was used as a carrier for the in situ reductive growth of gold nanoparticles (AuNPs) on its surface. Then NH2-MIL-101(Cr)@AuNPs were synergized with reduced graphene oxide (rGO) to amplify the electrochemical signals. The obtained NH2-MIL-101(Cr)@AuNPs/rGO nanocomposites exhibited electrical conductivity and stability. Mercaptosuccinic acid introduces a sufficiently large number of carboxyl groups by binding to AuNPs, providing abundant binding sites for ALP antibodies. The immunosensor used differential pulse voltammetry (DPV) for electrochemical analysis, and could capture the concentration response in the range of 10-12 −10-5 g mL−1 with a relatively low detection limit of 1.64 pg mL−1. In addition, the sensor has been successfully applied to the detection of ALP in massively diluted serum of fracture patients before and after drug administration.

A prototype of ultrasensitive time-resolved fluoroimmunoassay for the quantitation of lead in plasma using a fluorescence-enhanced europium chelate label for the detection system.

This study describes the prototype of a novel ultra-sensitive time-resolved fluoroimmunoassay (TRFIA) for the quantification of lead (Pb) in plasma. The assay procedures were conducted in 96-microwell plates and involved the competitive binding format. The assay used a mouse monoclonal antibody, designated as 2C33, that specifically recognized the diethylenetriamine pentaacetic acid chelate of Pb (Pb-DTPA) but did not recognize Pb-free DTPA chelator. The antigen used for coating onto the inner surfaces of assay plate microwells was Pb-DTPA conjugated with bovine serum albumin protein (Pb-DTPA-BSA). The competitive binding reaction occurred between Pb-DTPA chelates, formed in the sample solutions by treating the samples with an excess DTPA, and the coated Pb-DTPA-BSA for a limited quantity of 2C33 antibody binding sites. The antigen-antibody complex formed in the plate wells was quantified by a europium-DTPA-labeled secondary antibody and a fluorescence enhancement solution. The conditions of the assay were refined, and its optimum procedures were established. The TRFIA was validated following the immunoassay validation guidelines, and all of the validation criteria were acceptable. The working range of the assay was 20-300 pg mL-1 and its limit of quantitation was 20 pg mL-1. Metals that are commonly encountered in blood plasma did not interfere with Pb in the analysis by the proposed TRFIA. The assay was applied to the quantitation of Pb in plasma samples with satisfactory accuracy and precision. The results were compared favorably with those obtained by atomic emission spectroscopy. In conclusion, the present study represents the first TRFIA for the quantitation of Pb in plasma. The assay is superior to the existing atomic spectrometric methods and other immunoassays for Pb in terms of sensitivity, convenience, and analysis throughputs. The proposed TRFIA is anticipated to effectively contribute to assessing Pb concentrations and controlling the exposure of humans to its potential toxicity.

Detection of H. pylori outer membrane protein (HopQ) biomarker using electrochemical impedimetric immunosensor with polypyrrole nanotubes and carbon nanotubes nanocomposite on screen-printed carbon electrode

Helicobacter pylori (H. pylori) is classified as a class I carcinogen that colonizes the human gastrointestinal (GI) tract. The detection at low concentrations is crucial in combatting H. pylori. HopQ protein is located on H. pylori's outer membrane and is expressed at an early stage of contamination, which signifies it as an ideal biomarker. In this study, we presented the development of an electrochemical impedimetric immunosensor for the ultra-sensitive detection of HopQ at low concentrations. The sensor employed polypyrrole nanotubes (PPy-NTs) and carboxylated multi-walled carbon nanotubes (MWCNT-COOH) nanocomposite. PPy-NTs were chosen for their excellent conductivity, biocompatibility, and redox capabilities, simplifying sample preparation by eliminating the need to add redox probes upon measurement. MWCNT-COOH provided covalent binding sites for HopQ antibodies (HopQ-Ab) on the biosensor surface. Characterization of the biosensor was performed using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), contact angle measurements, and electrochemical impedance spectroscopy (EIS), complemented by numerical semiempirical quantum calculations. The results demonstrated a dynamic linear range of 5 pg/mL to 1.063 ng/mL and an excellent selectivity, with the possibility of excluding interference using EIS data, specifically charge transfer resistance and double-layer capacitance as multivariants for the calibration curve. Using two EIS components, the limit of detection is calculated to be 2.06 pg/mL. The biosensor was tested with a spiked drinking water sample and showed a signal recovery of 105.5% when detecting 300 pg/mL of HopQ. This novel H. pylori biosensor offers reliable, simple, portable, and rapid screening of the bacteria.

Impedimetric detection of gut-derived metabolites using 2D Germanene-based materials

Apart from the extensively researched graphene under the Group 14 2D materials, monolayered germanene and its derivatives have been gaining interest lately as alternative class of 2D materials owing to their facile synthesis, and attractive electronic and optical properties. Herein, three different functionalized germanene-based nanomaterials, namely Ge–H, Ge-CH3 and Ge–C3-CN were investigated on their novel incorporation in impedimetric immunosensors for the detection of gut-derived metabolites associated with neurological diseases, such as kynurenic acid (KA) and quinolinic acid (QA). The designed germanene-based immunosensor relies on an indirect competitive mechanism using disposable electrode printed chips. The competition for a fixed binding site of a primary antibody occurs between the bovine serum albumin-conjugated antigens on the electrode surface and the free antigens in the solution. Among the three materials, Ge–H displayed superior bioanalytical performance in KA and QA detection. Lower limits of detection of 5.07–11.38 ng/mL (26.79–68.11 nM) were attained for KA and QA with a faster reaction time than previously reported methods. Also, minimal cross-reactivity with interfering compounds, good reproducibility in impedimetric responses (RSD = 2.43–7.51 %) and long-term stability up to a month at 4 °C were the other attributes that the proposed Ge–H competitive impedimetric immunosensor has accomplished. The application of the developed Ge–H immunosensor to serum samples allowed an accurate KA and QA quantification at physiologically relevant levels. This work serves as a stepping-stone in the development of germanene-based nanomaterials for their implementation into cost-effective, miniaturized, portable and rapid impedimetric immunosensors, which are highly desirable for point-of-care testing in clinical settings.

Deep immunoglobulin repertoire sequencing depicts a comprehensive atlas of spike-specific antibody lineages shared among COVID-19 convalescents

ABSTRACT Neutralizing antibodies are a key component in protective humoral immunity against SARS-CoV-2. Currently, available technologies cannot track epitope-specific antibodies in global antibody repertoires. Thus, the comprehensive repertoire of spike-specific neutralizing antibodies elicited by SARS-CoV-2 infection is not fully understood. We therefore combined high-throughput immunoglobulin heavy chain (IgH) repertoire sequencing, and structural and bioinformatics analysis to establish an antibodyomics pipeline, which enables tracking spike-specific antibody lineages that target certain neutralizing epitopes. We mapped the neutralizing epitopes on the spike and determined the epitope-preferential antibody lineages. This analysis also revealed numerous overlaps between immunodominant neutralizing antibody-binding sites and mutation hotspots on spikes as observed so far in SARS-CoV-2 variants. By clustering 2677 spike-specific antibodies with 360 million IgH sequences that we sequenced, a total of 329 shared spike-specific antibody clonotypes were identified from 33 COVID-19 convalescents and 24 SARS-CoV-2-naïve individuals. Epitope mapping showed that the shared antibody responses target not only neutralizing epitopes on RBD and NTD but also non-neutralizing epitopes on S2. The immunodominance of neutralizing antibody response is determined by the occurrence of specific precursors in human naïve B-cell repertoires. We identified that only 28 out of the 329 shared spike-specific antibody clonotypes persisted for at least 12 months. Among them, long-lived IGHV3-53 antibodies are likely to evolve cross-reactivity to Omicron variants through accumulating somatic hypermutations. Altogether, we created a comprehensive atlas of spike-targeting antibody lineages in COVID-19 convalescents and antibody precursors in human naïve B cell repertoires, providing a valuable reference for future vaccine design and evaluation.