Antibodies targeting conserved non-canonical antigens and endemic coronaviruses associate with favorable outcomes in severe COVID-19

Sample-sparing multiplexed antibody Fc biomarker discovery using a reconfigurable integrated microfluidic platform

Control of endemic infectious diseases is often impeded by the lack of sensitive and specific yet easy-to-obtain biomarkers. Antibody fragment crystallizable (Fc) regions, such as Fc glycosylation, which are modulated in a pathogen-specific and disease-state-specific manner have emerged as potential such biomarkers. However current methods to perform large-scale antigen-specific antibody Fc feature screening for biomarker discovery often require too much sample volume, cost and expertise to be realistically realizable in many disease contexts. Here we present a simple, flexible and reconfigurable microfluidic device, made using rapid prototyping techniques, that can perform highly multiplexed and high-throughput biomarker discovery targeting both antibody fragment antigen-binding (Fab) and Fc features including antigen specificity, antibody isotypes, subclasses, N-glycosylation and Fc receptor binding. Using integration of an antigen microarray and reconfigurable microfluidics for sample and probe distribution, the device can perform a total of 1400 assays measuring 100 antibody Fab and Fc features per sample from a low sample volume (15 μL). The device demonstrates cleanroom-free simple fabrication and ease of use comparable to standard immunoassay platforms. Performance comparable to existing methods was validated and a biomarker screening for schistosomiasis, a helminth-mediated infection, was performed using clinical samples where antibody subclass-based biomarkers were successfully identified distinguishing current infection from former infection and endemic controls.

Neutralizing and enhancing monoclonal antibodies in SARS-CoV-2 convalescent patients: lessons from early variant infection and impact on shaping emerging variants

Serological studies of COVID-19 convalescent patients have identified polyclonal lineage-specific and cross-reactive antibodies (Abs), with varying effector functions against virus variants. Individual specificities of anti-SARS-CoV-2 Abs and their impact on infectivity by other variants have been little investigated to date. Here, we dissected at a monoclonal level neutralizing and enhancing Abs elicited by early variants and how they affect infectivity of emerging variants. B cells from 13 convalescent patients originally infected by D614G or Alpha variants were immortalized to isolate 445 naturally-produced anti-SARS-CoV-2 Abs. Monoclonal antibodies (mAbs) were tested for their abilities to impact the cytopathic effect of D614G, Delta, and Omicron (BA.1) variants. Ninety-eight exhibited robust neutralization against at least one of the three variant types, while 309 showed minimal or no impact on infectivity. Thirty-eight mAbs enhanced infectivity of SARS-CoV-2. Infection with D614G/Alpha variants generated variant-specific (65 neutralizing Abs, 35 enhancing Abs) and cross-reactive (18 neutralizing Abs, 3 enhancing Abs) mAbs. Interestingly, among the neutralizing mAbs with cross-reactivity restricted to two of the three variants tested, none demonstrated specific neutralization of the Delta and Omicron variants. In contrast, cross-reactive mAbs enhancing infectivity (n = 3) were found exclusively specific to Delta and Omicron variants. Notably, two mAbs that amplified in vitro the cytopathic effect of the Delta variant also exhibited neutralization against Omicron. These findings shed light on functional diversity of cross-reactive Abs generated during SARS-CoV-2 infection and illustrate how the balance between neutralizing and enhancing Abs facilitate variant emergence.

High throughput electronic detection of biomarkers using enzymatically amplified metallization on nanostructured surfaces

Enzyme-linked immunosorbent assays are commonly used for clinical biomarker detection. However, they remain resource-intensive and difficult to scale globally. Here we present a miniaturized direct electronic biosensing modality which generates a simple and sensitive, quantitative, resistive readout of analyte binding in immunoassays. It utilizes the enhanced metallization generated by synergistic catalytic activity of nanostructured surfaces, created using gold nanoparticles, with enzymatic metallization, catalyzed by analyte-bound enzyme-labeled antibodies, to create a connected metal layer between microelectrodes. Based on this scheme, we develop a portable, high-throughput electronic biomarker detection device and platform which allows testing 96 different low volume (3 μL) clinical samples in a handheld device. We find an analyte concentration-dependent tunable digital switch-like behavior in the measured resistance of this device. We use this system to further explore the mechanism of enhanced metallization and find optimal parameters. Finally, we use this platform to perform quantitative measurement of viral antigen-specific antibody titers from convalescent COVID-19 patient serum.

Deep humoral profiling coupled to interpretable machine learning unveils diagnostic markers and pathophysiology of schistosomiasis

Schistosomiasis, a highly prevalent parasitic disease, affects more than 200 million people worldwide. Current diagnostics based on parasite egg detection in stool detect infection only at a late stage, and current antibody-based tests cannot distinguish past from current infection. Here, we developed and used a multiplexed antibody profiling platform to obtain a comprehensive repertoire of antihelminth humoral profiles including isotype, subclass, Fc receptor (FcR) binding, and glycosylation profiles of antigen-specific antibodies. Using Essential Regression (ER) and SLIDE, interpretable machine learning methods, we identified latent factors (context-specific groups) that move beyond biomarkers and provide insights into the pathophysiology of different stages of schistosome infection. By comparing profiles of infected and healthy individuals, we identified modules with unique humoral signatures of active disease, including hallmark signatures of parasitic infection such as elevated immunoglobulin G4 (IgG4). However, we also captured previously uncharacterized humoral responses including elevated FcR binding and specific antibody glycoforms in patients with active infection, helping distinguish them from those without active infection but with equivalent antibody titers. This signature was validated in an independent cohort. Our approach also uncovered two distinct endotypes, nonpatent infection and prior infection, in those who were not actively infected. Higher amounts of IgG1 and FcR1/FcR3A binding were also found to be likely protective of the transition from nonpatent to active infection. Overall, we unveiled markers for antibody-based diagnostics and latent factors underlying the pathogenesis of schistosome infection. Our results suggest that selective antigen targeting could be useful in early detection, thus controlling infection severity.

SLIDE: Significant Latent Factor Interaction Discovery and Exploration across biological domains

Modern multiomic technologies can generate deep multiscale profiles. However, differences in data modalities, multicollinearity of the data, and large numbers of irrelevant features make analyses and integration of high-dimensional omic datasets challenging. Here we present Significant Latent Factor Interaction Discovery and Exploration (SLIDE), a first-in-class interpretable machine learning technique for identifying significant interacting latent factors underlying outcomes of interest from high-dimensional omic datasets. SLIDE makes no assumptions regarding data-generating mechanisms, comes with theoretical guarantees regarding identifiability of the latent factors/corresponding inference, and has rigorous false discovery rate control. Using SLIDE on single-cell and spatial omic datasets, we uncovered significant interacting latent factors underlying a range of molecular, cellular and organismal phenotypes. SLIDE outperforms/performs at least as well as a wide range of state-of-the-art approaches, including other latent factor approaches. More importantly, it provides biological inference beyond prediction that other methods do not afford. Thus, SLIDE is a versatile engine for biological discovery from modern multiomic datasets.

Impact of ageing on homologous and human-coronavirus-reactive antibodies after SARS-CoV-2 vaccination or infection

The endemic human coronaviruses (HCoVs) circulate worldwide yet remain understudied and unmitigated. The observation of elevated levels of HCoV reactive antibodies in COVID-19 patients highlights the urgent necessity of better understanding of HCoV specific immunity. Here, we characterized in-depth the de novo SARS-CoV-2 specific antibody responses and the boosting of HCoV-reactive antibodies after SARS-CoV-2 vaccination or infection in individuals up to 98 years old. All the vaccinees were home-dwelling with no documented SARS-CoV-2 infection before receiving the COVID-19 mRNA vaccine (BNT162b2). The first two vaccine doses elicited potent SARS-CoV-2 spike binding antibodies in individuals up to 80 years. The third dose largely boosted the previously low S2 domain binding and neutralizing antibodies in elderly 80-90 years old, but less so in those above 90 years. The endemic betacoronavirus (HKU1 and OC43) reactive antibodies were boosted in all vaccinees, although to a lesser extent in those above 80 years old. COVID-19 patients had potent elevation of alpha- and betacoronavirus (229E, NL63, HKU1 and OC43) reactive antibodies. In both patients and vaccinees, S2 domain specific antibody increases correlated with SARS-CoV-2 neutralizing and HCoV-reactive antibody responses in all ages, indicating S2 domain as a candidate for future universal coronavirus vaccine design.

Effect of seasonal coronavirus immune imprinting on the immunogenicity of inactivated COVID-19 vaccination

Background

Pre-existing cross-reactive immunity among different coronaviruses, also termed immune imprinting, may have a comprehensive impact on subsequent SARS-CoV-2 infection and COVID-19 vaccination effectiveness. Here, we aim to explore the interplay between pre-existing seasonal coronaviruses (sCoVs) antibodies and the humoral immunity induced by COVID-19 vaccination.

Methods

We first collected serum samples from healthy donors prior to COVID-19 pandemic and individuals who had received COVID-19 vaccination post-pandemic in China, and the levels of IgG antibodies against sCoVs and SARS-CoV-2 were detected by ELISA. Wilcoxon rank sum test and chi-square test were used to compare the difference in magnitude and seropositivity rate between two groups. Then, we recruited a longitudinal cohort to collect serum samples before and after COVID-19 vaccination. The levels of IgG antibodies against SARS-CoV-2 S, S1, S2 and N antigen were monitored. Association between pre-existing sCoVs antibody and COVID-19 vaccination-induced antibodies were analyzed by Spearman rank correlation.

Results

96.0% samples (339/353) showed the presence of IgG antibodies against at least one subtype of sCoVs. 229E and OC43 exhibited the highest seroprevalence rates at 78.5% and 72.0%, respectively, followed by NL63 (60.9%) and HKU1 (52.4%). The levels of IgG antibodies against two β coronaviruses (OC43 and HKU1) were significantly higher in these donors who had inoculated with COVID-19 vaccines compared to pre-pandemic healthy donors. However, we found that COVID-19 vaccine-induced antibody levels were not significant different between two groups with high levelor low level of pre-existing sCoVs antibody among the longitudinal cohort.

Conclusion

We found a high prevalence of antibodies against sCoVs in Chinese population. The immune imprinting by sCoVs could be reactivated by COVID-19 vaccination, but it did not appear to be a major factor affecting the immunogenicity of COVID-19 vaccine. These findings will provide insights into understanding the impact of immune imprinting on subsequent multiple shots of COVID-19 vaccines.

Electronic Immunoassay Using Enzymatic Metallization on Microparticles

We present here an inexpensive method for generating a sensitive direct electronic readout in bead-based immunoassays without the use of any intermediate optical instrumentation (e.g., lasers, photomultipliers, etc.). Analyte binding to capture antigen-coated beads or microparticles is converted to probe-directed enzymatically amplified silver metallization on microparticle surfaces. Individual microparticles are then rapidly characterized in a high-throughput manner via single-bead multifrequency electrical impedance spectra captured using a simple and inexpensive microfluidic impedance spectrometry system we develop here, where they flow through a three-dimensional (3D)-printed plastic microaperture sandwiched between plated through-hole electrodes on a printed circuit board. Metallized microparticles are found to have unique impedance signatures distinguishing them from unmetallized ones. Coupled with a machine learning algorithm, this enables a simple electronic readout of the silver metallization density on microparticle surfaces and hence the underlying analyte binding. Here, we also demonstrate the use of this scheme to measure the antibody response to the viral nucleocapsid protein in convalescent COVID-19 patient serum.

Endogenous piRNAs Can Interact with the Omicron Variant of the SARS-CoV-2 Genome

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which caused the COVID-19 pandemic, can still infect populations in many countries around the globe. The Omicron strain is the most mutated variant of SARS-CoV-2. The high transmissibility of the strain and its ability to evade immunity necessitate a priority study of its properties in order to quickly create effective means of preventing its spread. The current research aimed to examine the in silico interaction between PIWI-interacting RNAs (piRNAs) and the SARS-CoV-2 genome (gRNA) to identify endogenous piRNAs and propose synthetic piRNAs with strong antiviral activity for drug development. This study used validated bioinformatic approaches regarding the interaction of more than eight million piRNAs with the SARS-CoV-2 genome. The piRNAs’ binding sites (BSs) in the 5′UTR were located with overlapping nucleotide sequences termed clusters of BSs. Several BSs clusters have been found in the nsp3, nsp7, RNA-dependent RNA polymerase, endoRNAse, S surface glycoprotein, ORF7a, and nucleocapsid. Sixteen synthetic piRNAs that interact with gRNA have been proposed with free binding energy ranging from −170 kJ/mol to −175 kJ/mol, which can be used to create drugs that suppress the reproduction of SARS-CoV-2.

Inexpensive High-Throughput Multiplexed Biomarker Detection Using Enzymatic Metallization with Cellphone-Based Computer Vision

Multiplexed biomarker detection can play a critical role in reliable and comprehensive disease diagnosis and prediction of outcome. Enzyme-linked immunosorbent assay (ELISA) is the gold standard method for immunobinding-based biomarker detection. However, this is currently expensive, limited to centralized laboratories, and usually limited to the detection of a single biomarker at a time. We present a low-cost, smartphone-based portable biosensing platform for high-throughput, multiplexed, sensitive, and quantitative detection of biomarkers from single, low-volume drops (<1 μL) of clinical samples. Biomarker binding to spotted capture antigens is converted, via enzymatic metallization, to the localized surface deposition of amplified, dry-stable, silver metal spots whose darkness is proportional to biomarker concentration. A custom smartphone application is developed, which uses real-time computer vision to enable easy optical detection of the deposited metal spots and sensitive and reproducible quantification of the biomarkers. We demonstrate the use of this platform for high-throughput, multiplexed detection of multiple viral antigen-specific antibodies from convalescent COVID-19 patient serum as well as vaccine-elicited antibody responses from uninfected vaccine-recipient serum and show that distinct multiplexed antibody fingerprints are observed among them.

Can T Cells Abort SARS-CoV-2 and Other Viral Infections?

Despite the highly infectious nature of the SARS-CoV-2 virus, it is clear that some individuals with potential exposure, or even experimental challenge with the virus, resist developing a detectable infection. While a proportion of seronegative individuals will have completely avoided exposure to the virus, a growing body of evidence suggests a subset of individuals are exposed, but mediate rapid viral clearance before the infection is detected by PCR or seroconversion. This type of "abortive" infection likely represents a dead-end in transmission and precludes the possibility for development of disease. It is, therefore, a desirable outcome on exposure and a setting in which highly effective immunity can be studied. Here, we describe how early sampling of a new pandemic virus using sensitive immunoassays and a novel transcriptomic signature can identify abortive infections. Despite the challenges in identifying abortive infections, we highlight diverse lines of evidence supporting their occurrence. In particular, expansion of virus-specific T cells in seronegative individuals suggests abortive infections occur not only after exposure to SARS-CoV-2, but for other coronaviridae, and diverse viral infections of global health importance (e.g., HIV, HCV, HBV). We discuss unanswered questions related to abortive infection, such as: 'Are we just missing antibodies? Are T cells an epiphenomenon? What is the influence of the dose of viral inoculum?' Finally, we argue for a refinement of the current paradigm that T cells are only involved in clearing established infection; instead, we emphasise the importance of considering their role in terminating early viral replication by studying abortive infections.

Enhanced Enzymatically Amplified Metallization on Nanostructured Surfaces for Multiplexed Point-of-Care Electrical Detection of COVID-19 Biomarkers

Inexpensive yet sensitive and specific biomarker detection is a critical bottleneck in diagnostics, monitoring, and surveillance of infectious diseases such as COVID-19. Multiplexed detection of several biomarkers can achieve wider diagnostic applicability, accuracy, and ease-of-use, while reducing cost. Current biomarker detection methods often use enzyme-linked immunosorbent assays (ELISA) with optical detection which offers high sensitivity and specificity. However, this is complex, expensive, and limited to detecting only a single analyte at a time. Here, it is found that biomarker-bound enzyme-labeled probes act synergistically with nanostructured catalytic surfaces and can be used to selectively reduce a soluble silver substrate to generate highly dense and conductive, localized surface silver metallization on microelectrode arrays. This enables a sensitive and quantitative, simple, direct electronic readout of biomarker binding without the use of any intermediate optics. Furthermore, the localized and dry-phase stable nature of the metallization enables multiplexed electronic measurement of several biomarkers from a single drop (<10 µL) of sample on a microchip.This method is applied for the multiplexed point-of-care (POC) quantitative detection of multiple COVID-19 antigen-specific antibodies. Combining a simple microchip and an inexpensive, cellphone-interfaced, portable reader, the detection and discrimination of biomarkers of prior infection versus vaccination is demonstrated.