Dendritic-cell-targeting virus-like particles as potent mRNA vaccine carriers.

Messenger RNA vaccines lack specificity for dendritic cells (DCs)-the most effective cells at antigen presentation. Here we report the design and performance of a DC-targeting virus-like particle pseudotyped with an engineered Sindbis-virus glycoprotein that recognizes a surface protein on DCs, and packaging mRNA encoding for the Spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or for the glycoproteins B and D of herpes simplex virus 1. Injection of the DC-targeting SARS-CoV-2 mRNA vaccine in the footpad of mice led to substantially higher and durable antigen-specific immunoglobulin-G titres and cellular immune responses than untargeted virus-like particles and lipid-nanoparticle formulations. The vaccines also protected the mice from infection with SARS-CoV-2 or with herpes simplex virus 1. Virus-like particles with preferential uptake by DCs may facilitate the development of potent prophylactic and therapeutic vaccines.

Developing Deep LSTMs With Later Temporal Attention for Predicting COVID-19 Severity, Clinical Outcome, and Antibody Level by Screening Serological Indicators Over Time.

OBJECTIVE: The clinical course of COVID-19, as well as the immunological reaction, is notable for its extreme variability. Identifying the main associated factors might help understand the disease progression and physiological status of COVID-19 patients. The dynamic changes of the antibody against Spike protein are crucial for understanding the immune response. This work explores a temporal attention (TA) mechanism of deep learning to predict COVID-19 disease severity, clinical outcomes, and Spike antibody levels by screening serological indicators over time. METHODS: We use feature selection techniques to filter feature subsets that are highly correlated with the target. The specific deep Long Short-Term Memory (LSTM) models are employed to capture the dynamic changes of disease severity, clinical outcome, and Spike antibody level. We also propose deep LSTMs with a TA mechanism to emphasize the later blood test records because later records often attract more attention from doctors. RESULTS: Risk factors highly correlated with COVID-19 are revealed. LSTM achieves the highest classification accuracy for disease severity prediction. Temporal Attention Long Short-Term Memory (TA-LSTM) achieves the best performance for clinical outcome prediction. For Spike antibody level prediction, LSTM achieves the best permanence. CONCLUSION: The experimental results demonstrate the effectiveness of the proposed models. The proposed models can provide a computer-aided medical diagnostics system by simply using time series of serological indicators.

CRISPR-based diagnostics of different biomolecules from nucleic acids, proteins, and small molecules to exosomes.

CRISPR-based detection technologies have been widely explored for molecular diagnostics. However, the challenge lies in converting the signal of different biomolecules, such as nucleic acids, proteins, small molecules, exosomes, and ions, into a CRISPR-based nucleic acid detection signal. Understanding the detection of different biomolecules using CRISPR technology can aid in the development of practical and promising detection approaches. Unfortunately, existing reviews rarely provide an overview of CRISPR-based molecular diagnostics from the perspective of different biomolecules. Herein, we first introduce the principles and characteristics of various CRISPR nucleases for molecular diagnostics. Then, we focus on summarizing and evaluating the latest advancements in CRISPR-based detection of different biomolecules. Through a comparison of different methods of amplification and signal readout, we discuss how general detection methods can be integrated with CRISPR. Finally, we conclude by identifying opportunities for the improvement of CRISPR in quantitative, amplification-free, multiplex, all-in-one, and point-of-care testing (POCT) purposes.

Structural insights into RNase J that plays an essential role in Mycobacterium tuberculosis RNA metabolism.

Ribonucleases (RNases) are responsible for RNA metabolism. RNase J, the core enzyme of the RNA degradosome, plays an essential role in global mRNA decay. Emerging evidence showed that the RNase J of Mycobacterium tuberculosis (Mtb-RNase J) could be an excellent target for treating Mtb infection. Here, crystal structures of Mtb-RNase J in apo-state and complex with the single-strand RNA reveal the conformational change upon RNA binding and hydrolysis. Mtb-RNase J forms an active homodimer through the interactions between the ß-CASP and the ß-lactamase domain. Knockout of RNase J slows the growth rate and changes the colony morphologies and cell length in Mycobacterium smegmatis, which is restored by RNase J complementation. Finally, RNA-seq analysis shows that the knockout strain significantly changes the expression levels of 49 genes in metabolic pathways. Thus, our current study explores the structural basis of Mtb-RNase J and might provide a promising candidate in pharmacological treatment for tuberculosis.

Rapid and Accurate Detection of SARS-CoV-2 Using an iPad-Controlled, High-Throughput, Portable, and Multiplex Hive-Chip Platform (HiCube).

Rapid and accurate detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is one of the most effective measures to control the coronavirus disease 2019 (COVID-19) pandemic. However, there is still lack of an ideal detection platform capable of high sample throughput, portability, and multiplicity. Herein, by combining Hive-Chip (capillary microarray) and reverse transcriptional loop-mediated isothermal amplification (RT-LAMP), we developed an iPad-controlled, high-throughput (48 samples at one run), portable (smaller than a backpack), multiplex (monitoring 8 gene fragments in one reaction), and real-time detection platform for SARS-CoV-2 detection. This platform is composed of a portable Hive-Chip device (HiCube; 32.7 × 29.7 × 20 cm, 5 kg), custom-designed software, and optimized Hive-Chips. RT-LAMP primers targeting seven SARS-CoV-2 genes (S, E, M, N, ORF1ab, ORF3a, and ORF7a) and one positive control (human RNase P) were designed and prefixed in the Hive-Chip. On-chip RT-LAMP showed that the limit of detection (LOD) of SARS-CoV-2 synthetic RNAs is 1 copy/µL, and there is no cross-reaction among different target genes. The platform was validated by 100 clinical samples of SARS-CoV-2, and the results were highly consistent with those of the traditional real-time PCR assay. In addition, on-chip detection of 6 other respiratory pathogens showed no cross-reactivity. Overall, our platform has great potential for fast, accurate, and on-site detection of SARS-CoV-2.

Specific pupylation as IDEntity reporter (SPIDER) for the identification of protein-biomolecule interactions.

Protein-biomolecule interactions play pivotal roles in almost all biological processes. For a biomolecule of interest, the identification of the interacting protein(s) is essential. For this need, although many assays are available, highly robust and reliable methods are always desired. By combining a substrate-based proximity labeling activity from the pupylation pathway of Mycobacterium tuberculosis and the streptavidin (SA)-biotin system, we developed the Specific Pupylation as IDEntity Reporter (SPIDER) method for identifying protein-biomolecule interactions. Using SPIDER, we validated the interactions between the known binding proteins of protein, DNA, RNA, and small molecule. We successfully applied SPIDER to construct the global protein interactome for m6A and mRNA, identified a variety of uncharacterized m6A binding proteins, and validated SRSF7 as a potential m6A reader. We globally identified the binding proteins for lenalidomide and CobB. Moreover, we identified SARS-CoV-2-specific receptors on the cell membrane. Overall, SPIDER is powerful and highly accessible for the study of protein-biomolecule interactions.

Characterization and epitope mapping of monoclonal antibodies against PEDV N protein.

Porcine epidemic diarrhea virus (PEDV) causes acute diarrhea, vomiting, dehydration and high mortality in neonatal piglets. The nucleocapsid (N) protein of PEDV is a highly conserved protein with strong immunogenicity and palys an important role in PEDV diagnosis. However, epitopes on the PEDV N protein have not yet been well characterized. Here, 32 monoclonal antibodies (mAbs) against the PEDV N protein were produced and identified. Six new epitopes were first identified by using a high-throughput epitope mapping method named AbMap. Sequence analysis revealed that among the six epitopes five epitopes were highly conserved among different PEDV strains. We also confirmed that the mAbs derived from the six epitopes of PEDV N protein, have no cross-reactivity with transmissible gastro enteritis virus or porcine delta coronavirus. These mAbs and their defined epitopes will help to understand the N protein structure and immunological characteristics, and to develop a rapid, accurate PEDV diagnosis method.

Longitudinal neutralization activities on authentic Omicron variant provided by three doses of BBIBP-CorV vaccination during one year.

The majority of people in China have been immunized with the inactivated viral vaccine BBIBP-CorV. The emergence of the Omicron variant raised the concerns about protection efficacy of the inactivated viral vaccine in China. However, longitudinal neutralization data describing protection efficacy against Omicron variant is still lacking. Here we present one-year longitudinal neutralization data of BBIBP-CorV on authentic Omicron, Delta, and wild-type strains using 224 sera collected from 14 volunteers who have finished three doses BBIBP-CorV. The sera were also subjected for monitoring the SARS-CoV-2 specific IgG, IgA, and IgM responses on protein and peptide microarrays. The neutralization titers showed different protection efficacies against the three strains. By incorporating IgG and IgA signals of proteins and Spike protein derived peptide on microarray, panels as potential surrogate biomarkers for rapid estimation of neutralization titers were established. These data support the necessity of the 3rd dose of BBIBP-CorV vaccination. After further validation and assay development, the panels could be used for reliable, convenient and fast evaluation of the efficacy of vaccination.

Nucleic acid testing of SARS-CoV-2: A review of current methods, challenges, and prospects.

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has brought a huge threat to public health and the global economy. Rapid identification and isolation of SARS-CoV-2-infected individuals are regarded as one of the most effective measures to control the pandemic. Because of its high sensitivity and specificity, nucleic acid testing has become the major method of SARS-CoV-2 detection. A deep understanding of different diagnosis methods for COVID-19 could help researchers make an optimal choice in detecting COVID-19 at different symptom stages. In this review, we summarize and evaluate the latest developments in current nucleic acid detection methods for SARS-CoV-2. In particular, we discuss biosensors and CRISPR-based diagnostic systems and their characteristics and challenges. Furthermore, the emerging COVID-19 variants and their impact on SARS-CoV-2 diagnosis are systematically introduced and discussed. Considering the disease dynamics, we also recommend optional diagnostic tests for different symptom stages. From sample preparation to results readout, we conclude by pointing out the pain points and future directions of COVID-19 detection.

Identification of sitagliptin binding proteins by affinity purification mass spectrometry.

Type 2 diabetes mellitus (T2DM) is recognized as a serious public health concern with increasing incidence. The dipeptidyl peptidase-4 (DPP-4) inhibitor sitagliptin has been used for the treatment of T2DM worldwide. Although sitagliptin has excellent therapeutic outcome, adverse effects are observed. In addition, previous studies have suggested that sitagliptin may have pleiotropic effects other than treating T2DM. These pieces of evidence point to the importance of further investigation of the molecular mechanisms of sitagliptin, starting from the identification of sitagliptin-binding proteins. In this study, by combining affinity purification mass spectrometry (AP-MS) and stable isotope labeling by amino acids in cell culture (SILAC), we discover seven high-confidence targets that can interact with sitagliptin. Surface plasmon resonance (SPR) assay confirms the binding of sitagliptin to three proteins, i. e., LYPLAL1, TCP1, and CCAR2, with binding affinities (K D) ranging from 50.1 µM to 1490 µM. Molecular docking followed by molecular dynamic (MD) simulation reveals hydrogen binding between sitagliptin and the catalytic triad of LYPLAL1, and also between sitagliptin and the P-loop of ATP-binding pocket of TCP1. Molecular mechanics Poisson-Boltzmann Surface Area (MMPBSA) analysis indicates that sitagliptin can stably bind to LYPLAL1 and TCP1 in active sites, which may have an impact on the functions of these proteins. SPR analysis validates the binding affinity of sitagliptin to TCP1 mutant D88A is ~10 times lower than that to the wild-type TCP1. Our findings provide insights into the sitagliptin-targets interplay and demonstrate the potential of sitagliptin in regulating gluconeogenesis and in anti-tumor drug development.

Age- and Severity-Associated Humoral Immunity Response in COVID-19 Patients: A Cohort Study from Wuhan, China.

Age has been found to be the single most significant factor in COVID-19 severity and outcome. However, the age-related severity factors of COVID-19 have not been definitively established. In this study, we detected SARS-CoV-2-specific antibody responses and infectious disease-related blood indicators in 2360 sera from 783 COVID-19 patients, with an age range of 1−92 years. In addition, we recorded the individual information and clinical symptoms of the patients. We found that the IgG responses for S1, N, and ORF3a and the IgM for NSP7 were associated with severe COVID-19 at different ages. The IgM responses for the S-protein peptides S1-113 (aa 673−684) and S2-97 (aa 1262−1273) were associated with severe COVID-19 in patients aged <60. Furthermore, we found that the IgM for S1-113 and NSP7 may play a protective role in patients aged <60 and >80, respectively. Regarding clinical parameters, we analyzed the diagnostic ability of five clinical parameters for severe COVID-19 in six age groups and identified three-target panel, glucose, IL-6, myoglobin, IL-6, and NT proBNP as the appropriate diagnostic markers for severe COVID-19 in patients aged <41, 41−50, 51−60, 61−70, 71−80, and >80, respectively. The age-associated severity factors revealed here will facilitate our understanding of COVID-19 immunity and diagnosis, and eventually provide meaningful information for combating the pandemic.

Ultrasensitive monitoring of SARS-CoV-2-specific antibody responses based on a digital approach reveals one week of IgG seroconversion.

COVID-19 is still unfolding, while many people have been vaccinated. In comparison to nucleic acid testing (NAT), antibody-based immunoassays are faster and more convenient. However, its application has been hampered by its lower sensitivity and the existing fact that by traditional immunoassays, the measurable seroconversion time of pathogen-specific antibodies, such as IgM or IgG, lags far behind that of nucleic acids. Herein, by combining the single molecule array platform (Simoa), RBD, and a previously identified SARS-CoV-2 S2 protein derivatized 12-aa peptide (S2-78), we developed and optimized an ultrasensitive assay (UIM-COVID-19 assay). Sera collected from three sources were tested, i.e., convalescents, inactivated virus vaccine-immunized donors and wild-type authentic SARS-CoV-2-infected rhesus monkeys. The sensitivities of UIM-COVID-19 assays are 100-10,000 times higher than those of conventional flow cytometry, which is a relatively sensitive detection method at present. For the established UIM-COVID-19 assay using RBD as a probe, the IgG and IgM seroconversion times after vaccination were 7.5 and 8.6 days vs. 21.4 and 24 days for the flow cytometry assay, respectively. In addition, using S2-78 as a probe, the UIM-COVID-19 assay could differentiate COVID-19 patients (convalescents) from healthy people and patients with other diseases, with AUCs ranging from 0.85-0.95. In summary, the UIM-COVID-19 we developed here is a promising ultrasensitive biodetection strategy that has the potential to be applied for both immunological studies and diagnostics.

Current advances in antibody-based serum biomarker studies: From protein microarray to phage display.

PURPOSE: This review aims to summarize the technological advances in the field of antibody-based biomarker studies by proteome microarray and phage display. In addition, the possible development directions of this field are also discussed. EXPERIMENTAL DESIGN: We have focused on the antibody profiling by proteome microarray and phage display, including the technological advances, the tools/resources constructed, and the characteristics of both platforms. RESULTS: With the help of tools/resources and technological advances in proteome microarray and phage display, the efficiency of profiling antibody-based biomarkers in serum samples has been greatly improved. CONCLUSIONS: In the past few years, proteome microarray and phage display, especially the latter one, have already demonstrated their capacity and efficiency for biomarker identification. In the near future, we believe that more antibody-based biomarkers could be identified, and some of them could eventually be developed into real clinical applications.

Evaluation of Spike Protein Epitopes by Assessing the Dynamics of Humoral Immune Responses in Moderate COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic is caused by a novel coronavirus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The spike protein (S) of SARS-CoV-2 is a major target for diagnosis and vaccine development because of its essential role in viral infection and host immunity. Currently, time-dependent responses of humoral immune system against various S protein epitopes are poorly understood. In this study, enzyme-linked immunosorbent assay (ELISA), peptide microarray, and antibody binding epitope mapping (AbMap) techniques were used to systematically analyze the dynamic changes of humoral immune responses against the S protein in a small cohort of moderate COVID-19 patients who were hospitalized for approximately two months after symptom onset. Recombinant truncated S proteins, target S peptides, and random peptides were used as antigens in the analyses. The assays demonstrated the dynamic IgM- and IgG recognition and reactivity against various S protein epitopes with patient-dependent patterns. Comprehensive analysis of epitope distribution along the spike gene sequence and spatial structure of the homotrimer S protein demonstrated that most IgM- and IgG-reactive peptides were clustered into similar genomic regions and were located at accessible domains. Seven S peptides were generally recognized by IgG antibodies derived from serum samples of all COVID-19 patients. The dynamic immune recognition signals from these seven S peptides were comparable to those of the entire S protein or truncated S1 protein. This suggested that the humoral immune system recognized few conserved S protein epitopes in most COVID-19 patients during the entire duration of humoral immune response after symptom onset. Furthermore, in this cohort, individual patients demonstrated stable immune recognition to certain S protein epitopes throughout their hospitalization period. Therefore, the dynamic characteristics of humoral immune responses to S protein have provided valuable information for accurate diagnosis and immunotherapy of COVID-19 patients.

SARS-CoV-2 proteome microarray for COVID-19 patient sera profiling.

The immunogenicity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteome is largely unknown. Here we describe a protocol for analyzing sera samples with SARS-CoV-2 proteome microarray. The proteins were expressed by either E. coli expression system or eukaryotic cell expression systems and obtained by affinity purification. The protocol includes microarray fabricating and sera profiling, which will be used to build an antibody response landscape for IgG and IgM. The protocol may help to facilitate a deeper understanding of immunity related to SARS-CoV-2. For complete details on the use and execution of this protocol, please refer to Li et al. (2021c).

Anti-SARS-CoV-2 IgG responses are powerful predicting signatures for the outcome of COVID-19 patients.

Introduction: The COVID-19 global pandemic is far from ending. There is an urgent need to identify applicable biomarkers for early predicting the outcome of COVID-19. Growing evidences have revealed that SARS-CoV-2 specific antibodies evolved with disease progression and severity in COIVD-19 patients. Objectives: We assumed that antibodies may serve as biomarkers for predicting the clinical outcome of hospitalized COVID-19 patients on admission. Methods: By taking advantage of a newly developed SARS-CoV-2 proteome microarray, we surveyed IgG responses against 20 proteins of SARS-CoV-2 in 1034 hospitalized COVID-19 patients on admission and followed till 66 days. The microarray results were further correlated with clinical information, laboratory test results and patient outcomes. Cox proportional hazards model was used to explore the association between SARS-CoV-2 specific antibodies and COVID-19 mortality. Results: Nonsurvivors (n = 955) induced higher levels of IgG responses against most of non-structural proteins than survivors (n = 79) on admission. In particular, the magnitude of IgG antibodies against 8 non-structural proteins (NSP1, NSP4, NSP7, NSP8, NSP9, NSP10, RdRp, and NSP14) and 2 accessory proteins (ORF3b and ORF9b) possessed significant predictive power for patient death, even after further adjustments for demographics, comorbidities, and common laboratory biomarkers for disease severity (all with p trend < 0.05). Additionally, IgG responses to all of these 10 non-structural/accessory proteins were also associated with the severity of disease, and differential kinetics and serum positive rate of these IgG responses were confirmed in COVID-19 patients of varying severities within 20 days after symptoms onset. The area under curves (AUCs) for these IgG responses, determined by computational cross-validations, were between 0.62 and 0.71. Conclusions: Our findings might have important implications for improving clinical management of COVID-19 patients.