Landscape of humoral immune responses against SARS-CoV-2 in patients with COVID-19 disease and the value of antibody testing

Integrative analysis of taurine metabolism-related genes prognostic signature with immunotherapy and identification of ABCB1 and GORASP1 as key genes in nasopharyngeal carcinoma

Taurine is an amino acid with several physiological functions and has been shown to be involved in the anti-tumor of human nasopharyngeal carcinoma (NPC) cells. However, the role of taurine metabolism-related genes (TMRGs) in NPC has not been reported. We integrated data from the Genecards, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Expression Omnibus(GEO) databases to identify differentially expressed genes associated with taurine metabolism in NPC patients. Gene Ontology (GO) and KEGG analyses were conducted to investigate the underlying mechanisms. Subsequently, Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses were performed to construct a taurine metabolism-related prognostic signature. Survival, medication sensitivity, and immunological microenvironment evaluations were performed to assess the prognostic utility of the model. Finally, immunohistochemistry (IHC) experiments were performed to validate the model's prognostic reliability. In addition, we further verified the reliability of our research results through molecular docking and single-cell sequencing. Our prognostic model was based on three pivotal TMRGs (ABCB1, GORASP1, and EZH2). Functional analysis revealed a strong association between TMRGs and miRNAs in cancer. Notably, increased risk scores correlated with worsening tumor malignancy and prognosis. Significant disparities in immune microenvironment, immune checkpoints, and drug sensitivity were observed between the high- and low-risk groups. The protein expression patterns of the selected genes in clinical NPC samples were validated using immunohistochemistry. Molecular docking verified the interaction between these three core genes and taurine, which was further supported by single-cell sequencing showing significant expression variation among different cell clusters in NPC. We had elucidated the functions, therapeutic potential, and prognostic significance of three key genes related to taurine metabolism in NPC through multidimensional research and experimental validation. This research provided valuable insights and potential avenues for improved NPC management.

Divergent autoantibody and cytokine levels in COVID-19 sepsis patients influence survival

Studies have pointed to a decisive role of autoantibodies in the context of sepsis and severe Coronavirus disease 2019 (COVID-19), which itself often fulfills the criteria for sepsis, including dysregulated immune responses and organ dysfunction. To directly compare and further analyze the autoantibody profiles of sepsis patients with and without COVID-19, the luciferase immunoprecipitation systems (LIPS) assay was used to measure the levels of autoantibodies against a variety of clinically relevant cytokines, lung-associated proteins, other autoantigens, and antibodies against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In addition, cytokine titers were measured with the LEGENDplex™ Human Antivirus Response Panel. We observed significantly increased levels of autoantibodies in 59% of the COVID-19-Sepsis group compared to 48% of the Sepsis group. Significant differences were identified between the groups for the levels of autoantibodies against gATPase. The cytokine levels of interferon (IFN)-λ1 and IP-10 were higher in the COVID-19-Sepsis group compared to the Sepsis group. Additional correlations between autoantibodies, cytokines and 30-day survival could be demonstrated, suggesting varied underlying pathological mechanisms. Elevated levels of cytokines and autoantibodies may serve as prognostic indicators for the survival probability of sepsis patients, highlighting the intricate relationship between immune responses and patient outcomes in the context of both sepsis and COVID-19.

MOI is a comprehensive database collecting processed multi-omics data associated with viral infection

Viral infections pose significant public health challenges, exemplified by the global impact of COVID-19 caused by SARS-CoV-2. Understanding the intricate molecular mechanisms governing virus-host interactions is pivotal for effective intervention strategies. Despite the burgeoning multi-omics data on viral infections, a centralized database elucidating host responses to viruses remains lacking. In response, we have developed a comprehensive database named 'MOI' (available at http://www.fynn-guo.cn/ ), specifically designed to aggregate processed Multi-Omics data related to viral Infections. This meticulously curated database serves as a valuable resource for conducting detailed investigations into virus-host interactions. Leveraging high-throughput sequencing data and metadata from PubMed and Gene Expression Omnibus (GEO), MOI comprises over 3200 viral-infected samples, encompassing human and murine infections. Standardized processing pipelines ensure data integrity, including bulk RNA sequencing (RNA-seq), single-cell RNA-seq (scRNA-seq), Chromatin Immunoprecipitation sequencing (ChIP-seq), and Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq). MOI offers user-friendly interfaces presenting comprehensive cell marker tables, gene expression data, and epigenetic landscape charts. Analytical tools for DNA sequence conversion, FPKM calculation, differential gene expression, and Gene Ontology (GO)/ Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment enhance data interpretation. Additionally, MOI provides 16 visualization plots for intuitive data exploration. In summary, MOI serves as a valuable repository for researchers investigating virus-host interactions. By centralizing and facilitating access to multi-omics data, MOI aims to advance our understanding of viral pathogenesis and expedite the development of therapeutic interventions.

Characterization of unique pattern of immune cell profile in patients with nasopharyngeal carcinoma through flow cytometry and machine learning

In patients with nasopharyngeal carcinoma (NPC), the alteration of immune responses in peripheral blood remains unclear. In this study, we established an immune cell profile for patients with NPC and used flow cytometry and machine learning (ML) to identify the characteristics of this profile. After isolation of circulating leukocytes, the proportions of 104 immune cell subsets were compared between NPC group and the healthy control group (HC). Data obtained from the immune cell profile were subjected to ML training to differentiate between the immune cell profiles of the NPC and HC groups. We observed that subjects in the NPC group presented higher proportions of T cells, memory B cells, short-lived plasma cells, IgG-positive B cells, regulatory T cells, MHC II+ T cells, CTLA4+ T cells and PD-1+ T cells than subjects in the HC group, indicating weaker and compromised cellular and humoral immune responses. ML revealed that monocytes, PD-1+ CD4 T cells, memory B cells, CTLA4+ CD4 Treg cells and PD-1+ CD8 T cells were strongly contributed to the difference in immune cell profiles between the NPC and HC groups. This alteration can be fundamental in developing novel immunotherapies for NPC.

[Evaluation of immunotoxicitiy in biomedical research and development]

Immunotoxicology aims at studying toxic effects of any substance on the immune system and its functions. In its various fields of application, this science is dependent on regulatory texts and guidelines. Studies are based on in vitro, ex vivo and in vivo techniques and are observational or functional allowing the identification of a toxic effect and its underlying mechanisms, respectively. Here, we review the various tests to perform in biomedical research and development, with a particular interest for the T-cell Dependent Antibody Response (TDAR) assay. We also briefly discuss the upcoming evolutions in this domain within a more ethically sound framework such as limiting the use of laboratory animals. These evolutions are represented by the development of relevant cell models.

Next Generation Sequencing Approaches to Characterize the Respiratory Tract Virome

The COVID-19 pandemic and heightened perception of the risk of emerging viral infections have boosted the efforts to better understand the virome or complete repertoire of viruses in health and disease, with a focus on infectious respiratory diseases. Next-generation sequencing (NGS) is widely used to study microorganisms, allowing the elucidation of bacteria and viruses inhabiting different body systems and identifying new pathogens. However, NGS studies suffer from a lack of standardization, in particular, due to various methodological approaches and no single format for processing the results. Here, we review the main methodological approaches and key stages for studies of the human virome, with an emphasis on virome changes during acute respiratory viral infection, with applications for clinical diagnostics and epidemiologic analyses.

Low quantity and quality of anti-spike humoral response is linked to CD4 T-cell apoptosis in COVID-19 patients

In addition to an inflammatory reaction, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)-infected patients present lymphopenia, which we recently reported as being related to abnormal programmed cell death. As an efficient humoral response requires CD4 T-cell help, we hypothesized that the propensity of CD4 T cells to die may impact the quantity and quality of the humoral response in acutely infected individuals. In addition to specific immunoglobulins (Ig)A, IgM, and IgG against SARS-CoV-2 nucleocapsid (N), membrane (M), and spike (S1) proteins, we assessed the quality of IgG response by measuring the avidity index. Because the S protein represents the main target for neutralization and antibody-dependent cellular cytotoxicity responses, we also analyzed anti-S-specific IgG using S-transfected cells (S-Flow). Our results demonstrated that most COVID-19 patients have a predominant IgA anti-N humoral response during the early phase of infection. This specific humoral response preceded the anti-S1 in time and magnitude. The avidity index of anti-S1 IgG was low in acutely infected individuals compared to convalescent patients. We showed that the percentage of apoptotic CD4 T cells is inversely correlated with the levels of specific IgG antibodies. These lower levels were also correlated positively with plasma levels of CXCL10, a marker of disease severity, and soluble Fas ligand that contributes to T-cell death. Finally, we found lower S-Flow responses in patients with higher CD4 T-cell apoptosis. Altogether, these results demonstrate that individuals with high levels of CD4 T-cell apoptosis and CXCL10 have a poor ability to build an efficient anti-S response. Consequently, preventing CD4 T-cell death might be a strategy for improving humoral response during the acute phase, thereby reducing COVID-19 pathogenicity.

Influenza A, Influenza B, and SARS-CoV-2 Similarities and Differences – A Focus on Diagnosis

In late December 2019, the first cases of viral pneumonia caused by an unidentified pathogen were reported in China. Two years later, SARS-CoV-2 was responsible for almost 450 million cases, claiming more than 6 million lives. The COVID-19 pandemic strained the limits of healthcare systems all across the world. Identifying viral RNA through real-time reverse transcription-polymerase chain reaction remains the gold standard in diagnosing SARS-CoV-2 infection. However, equipment cost, availability, and the need for trained personnel limited testing capacity. Through an unprecedented research effort, new diagnostic techniques such as rapid diagnostic testing, isothermal amplification techniques, and next-generation sequencing were developed, enabling accurate and accessible diagnosis. Influenza viruses are responsible for seasonal outbreaks infecting up to a quarter of the human population worldwide. Influenza and SARS-CoV-2 present with flu-like symptoms, making the differential diagnosis challenging solely on clinical presentation. Healthcare systems are likely to be faced with overlapping SARS-CoV-2 and Influenza outbreaks. This review aims to present the similarities and differences of both infections while focusing on the diagnosis. We discuss the clinical presentation of Influenza and SARS-CoV-2 and techniques available for diagnosis. Furthermore, we summarize available data regarding the multiplex diagnostic assay of both viral infections.

MVIP: multi-omics portal of viral infection

Virus infections are huge threats to living organisms and cause many diseases, such as COVID-19 caused by SARS-CoV-2, which has led to millions of deaths. To develop effective strategies to control viral infection, we need to understand its molecular events in host cells. Virus related functional genomic datasets are growing rapidly, however, an integrative platform for systematically investigating host responses to viruses is missing. Here, we developed a user-friendly multi-omics portal of viral infection named as MVIP (https://mvip.whu.edu.cn/). We manually collected available high-throughput sequencing data under viral infection, and unified their detailed metadata including virus, host species, infection time, assay, and target, etc. We processed multi-layered omics data of more than 4900 viral infected samples from 77 viruses and 33 host species with standard pipelines, including RNA-seq, ChIP-seq, and CLIP-seq, etc. In addition, we integrated these genome-wide signals into customized genome browsers, and developed multiple dynamic charts to exhibit the information, such as time-course dynamic and differential gene expression profiles, alternative splicing changes and enriched GO/KEGG terms. Furthermore, we implemented several tools for efficiently mining the virus-host interactions by virus, host and genes. MVIP would help users to retrieve large-scale functional information and promote the understanding of virus-host interactions.

AuNP Coupled Rapid Flow-Through Dot-Blot Immuno-Assay for Enhanced Detection of SARS-CoV-2 Specific Nucleocapsid and Receptor Binding Domain IgG

BACKGROUND

Serological tests detecting severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) are widely used in seroprevalence studies and evaluating the efficacy of the vaccination program. Some of the widely used serological testing techniques are enzyme-linked immune-sorbent assay (ELISA), chemiluminescence immunoassay (CLIA), and lateral flow immunoassay (LFIA). However, these tests are plagued with low sensitivity or specificity, time-consuming, labor-intensive, and expensive. We developed a serological test implementing flow-through dot-blot assay (FT-DBA) for SARS-CoV-2 specific IgG detection, which provides enhanced sensitivity and specificity while being quick to perform and easy to use.

METHODS

SARS-CoV-2 antigens were immobilized on nitrocellulose membrane to capture human IgG, which was then detected with anti-human IgG conjugated gold nanoparticle (hIgG-AuNP). A total of 181 samples were analyzed in-house. Within which 35 were further evaluated in US FDA-approved CLIA Elecsys SARS-CoV-2 assay. The positive panel consisted of RT-qPCR positive samples from patients with both <14 days and >14 days from the onset of clinical symptoms. The negative panel contained samples collected from the pre-pandemic era dengue patients and healthy donors during the pandemic. Moreover, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of FT-DBA were evaluated against RT-qPCR positive sera. However, the overall efficacies were assessed with sera that seroconverted against either nucleocapsid (NCP) or receptor-binding domain (RBD).

RESULTS

In-house ELISA selected a total of 81 true seropositive and 100 seronegative samples. The sensitivity of samples with <14 days using FT-DBA was 94.7%, increasing to 100% for samples >14 days. The overall detection sensitivity and specificity were 98.8% and 98%, respectively, whereas the overall PPV and NPV were 99.6% and 99%. Moreover, comparative analysis between in-house ELISA assays and FT-DBA revealed clinical agreement of Cohen's Kappa value of 0.944. The FT-DBA showed sensitivity and specificity of 100% when compared with commercial CLIA kits.

CONCLUSION

The assay can confirm past SARS-CoV-2 infection with high accuracy within 2 minutes compared to commercial CLIA or in-house ELISA. It can help track SARS-CoV-2 disease progression, population screening, and vaccination response. The ease of use of the assay without requiring any instruments while being semi-quantitative provides the avenue of its implementation in remote areas around the globe, where conventional serodiagnosis is not feasible.

Preexisting vs. de novo antibodies against SARS-CoV-2 in individuals without or with virus infection: impact on antibody therapy, vaccine research and serological testing

The causative agent of the ongoing pandemic in the world is SARS-CoV-2. The research on SARS-CoV-2 has progressed with lightning speed on various fronts, including clinical research and treatment, virology, epidemiology, drug development, and vaccine research. Recent studies reported that sera from healthy individuals, who were confirmed negative for SARS-CoV-2 by RT-PCR method, tested positive for antibodies against spike and nucleocapsid proteins of SARS-CoV-2. Further, such antibodies also exhibited neutralizing activity against the virus. These observations have prompted us to prepare a commentary on this topic. While the preexisting antibodies are likely to protect against SARS-CoV-2 infection, they may also complicate serological testing results. Another unknown is the influence of preexisting antibodies on immune responses in individuals receiving vaccines against  SARS-CoV-2. The commentary identifies the potential limitations with the serological tests based on spike and nucleocapsid proteins as these tests may overestimate the seroprevalence due to cross-reactive antibodies. The inclusion of tests specific to SARS-CoV-2 (such as RBD of spike protein) could overcome these limitations.

Methods of Respiratory Virus Detection: Advances towards Point-of-Care for Early Intervention

Respiratory viral infections threaten human life and inflict an enormous healthcare burden worldwide. Frequent monitoring of viral antibodies and viral load can effectively help to control the spread of the virus and make timely interventions. However, current methods for detecting viral load require dedicated personnel and are time-consuming. Additionally, COVID-19 detection is generally relied on an automated PCR analyzer, which is highly instrument-dependent and expensive. As such, emerging technologies in the development of respiratory viral load assays for point-of-care (POC) testing are urgently needed for viral screening. Recent advances in loop-mediated isothermal amplification (LAMP), biosensors, nanotechnology-based paper strips and microfluidics offer new strategies to develop a rapid, low-cost, and user-friendly respiratory viral monitoring platform. In this review, we summarized the traditional methods in respiratory virus detection and present the state-of-art technologies in the monitoring of respiratory virus at POC.