SARS-CoV-2 infection paralyzes cytotoxic and metabolic functions of the immune cells

A comprehensive SARS-CoV-2 and COVID-19 review, Part 2: host extracellular to systemic effects of SARS-CoV-2 infection

COVID-19, the disease caused by SARS-CoV-2, has caused significant morbidity and mortality worldwide. The betacoronavirus continues to evolve with global health implications as we race to learn more to curb its transmission, evolution, and sequelae. The focus of this review, the second of a three-part series, is on the biological effects of the SARS-CoV-2 virus on post-acute disease in the context of tissue and organ adaptations and damage. We highlight the current knowledge and describe how virological, animal, and clinical studies have shed light on the mechanisms driving the varied clinical diagnoses and observations of COVID-19 patients. Moreover, we describe how investigations into SARS-CoV-2 effects have informed the understanding of viral pathogenesis and provide innovative pathways for future research on the mechanisms of viral diseases.

Temporal Dynamics of Serum Perforin and Granzyme during the Acute Phase of SARS-CoV-2 Infection

BACKGROUND

As many SARS-CoV-2 infections are asymptomatic, it could be useful to be able to determine how much time has passed since infection. We explored the changes in the temporal levels of T cell-related proteins (including perforin and granzymes) in the sera of patients with SARS-CoV-2 infection using a commercially available assay.

METHODS

This study enrolled 36 patients infected with SARS-CoV-2 and 20 healthy control participants. Blood samples were collected at three different times based on the number of days since symptom onset (early phase: 1-5 days, mid-phase: 6-10 days, late phase: 11-18 days). We assessed the temporal changes in the serum levels of perforin and granzymes in patients with SARS-CoV-2 infection by comparing the results with those obtained in the healthy control group.

RESULTS

We identified a significantly low level of perforin in the early phase of SARS-CoV-2 infection (p < 0.01), which was restored to normal during the mid- and late phases of the infection. However, there was no difference in the temporal change in the level of granzymes in SARS-CoV-2-infected patients compared to the healthy control group.

CONCLUSIONS

This finding suggests that SARS-CoV-2 infection paralyzed the perforin expression in the early period immediately after infection. Thus, serum perforin is a potential marker for identifying the acute phase of SARS-CoV-2 infection.

Maintained imbalance of triglycerides, apolipoproteins, energy metabolites and cytokines in long-term COVID-19 syndrome patients

Background

Deep metabolomic, proteomic and immunologic phenotyping of patients suffering from an infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have matched a wide diversity of clinical symptoms with potential biomarkers for coronavirus disease 2019 (COVID-19). Several studies have described the role of small as well as complex molecules such as metabolites, cytokines, chemokines and lipoproteins during infection and in recovered patients. In fact, after an acute SARS-CoV-2 viral infection almost 10-20% of patients experience persistent symptoms post 12 weeks of recovery defined as long-term COVID-19 syndrome (LTCS) or long post-acute COVID-19 syndrome (PACS). Emerging evidence revealed that a dysregulated immune system and persisting inflammation could be one of the key drivers of LTCS. However, how these biomolecules altogether govern pathophysiology is largely underexplored. Thus, a clear understanding of how these parameters within an integrated fashion could predict the disease course would help to stratify LTCS patients from acute COVID-19 or recovered patients. This could even allow to elucidation of a potential mechanistic role of these biomolecules during the disease course.

Methods

This study comprised subjects with acute COVID-19 (n=7; longitudinal), LTCS (n=33), Recov (n=12), and no history of positive testing (n=73). ¹H-NMR-based metabolomics with IVDr standard operating procedures verified and phenotyped all blood samples by quantifying 38 metabolites and 112 lipoprotein properties. Univariate and multivariate statistics identified NMR-based and cytokine changes.

Results

Here, we report on an integrated analysis of serum/plasma by NMR spectroscopy and flow cytometry-based cytokines/chemokines quantification in LTCS patients. We identified that in LTCS patients lactate and pyruvate were significantly different from either healthy controls (HC) or acute COVID-19 patients. Subsequently, correlation analysis in LTCS group only among cytokines and amino acids revealed that histidine and glutamine were uniquely attributed mainly with pro-inflammatory cytokines. Of note, triglycerides and several lipoproteins (apolipoproteins Apo-A1 and A2) in LTCS patients demonstrate COVID-19-like alterations compared with HC. Interestingly, LTCS and acute COVID-19 samples were distinguished mostly by their phenylalanine, 3-hydroxybutyrate (3-HB) and glucose concentrations, illustrating an imbalanced energy metabolism. Most of the cytokines and chemokines were present at low levels in LTCS patients compared with HC except for IL-18 chemokine, which tended to be higher in LTCS patients.

Conclusion

The identification of these persisting plasma metabolites, lipoprotein and inflammation alterations will help to better stratify LTCS patients from other diseases and could help to predict ongoing severity of LTCS patients.

A metabolic blueprint of COVID-19 and long-term vaccine efficacy

Viruses are obligatory protein-coated units and often utilize the metabolic functions of the cells they infect. Viruses hijack cellular metabolic functions and cause consequences that can range from minor to devastating, as we have all witnessed during the COVID-19 pandemic. For understanding the virus-driven pathogenesis and its implications on the host, the cellular metabolism needs to be elucidated. How SARS-CoV-2 triggers metabolic functions and rewires the metabolism remains unidentified but the implications of the metabolic patterns are under investigation by several researchers. In this review, we have described the SARS-CoV-2-mediated metabolic alterations from in vitro studies to metabolic changes reported in victims of COVID-19. We have also discussed potential therapeutic targets to diminish the viral infection and suppress the inflammatory response, with respect to evidenced studies based on COVID-19 research. Finally, we aimed to explain how we could extend vaccine-induced immunity in people by targeting the immunometabolism.

Quantitative Serum NMR Spectroscopy Stratifies COVID-19 Patients and Sheds Light on Interfaces of Host Metabolism and the Immune Response with Cytokines and Clinical Parameters

The complex manifestations of COVID-19 are still not fully decoded on the molecular level. We combined quantitative the nuclear magnetic resonance (NMR) spectroscopy serum analysis of metabolites, lipoproteins and inflammation markers with clinical parameters and a targeted cytokine panel to characterize COVID-19 in a large (534 patient samples, 305 controls) outpatient cohort of recently tested PCR-positive patients. The COVID-19 cohort consisted of patients who were predominantly in the initial phase of the disease and mostly exhibited a milder disease course. Concerning the metabolic profiles of SARS-CoV-2-infected patients, we identified markers of oxidative stress and a severe dysregulation of energy metabolism. NMR markers, such as phenylalanine, inflammatory glycoproteins (Glyc) and their ratio with the previously reported supramolecular phospholipid composite (Glyc/SPC), showed a predictive power comparable to laboratory parameters such as C-reactive protein (CRP) or ferritin. We demonstrated interfaces between the metabolism and the immune system, e.g., we could trace an interleukin (IL-6)-induced transformation of a high-density lipoprotein (HDL) to a pro-inflammatory actor. Finally, we showed that metadata such as age, sex and constitution (e.g., body mass index, BMI) need to be considered when exploring new biomarkers and that adding NMR parameters to existing diagnoses expands the diagnostic toolbox for patient stratification and personalized medicine.

Integrative transcriptome analysis of SARS-CoV-2 human-infected cells combined with deep learning algorithms identifies two potential cellular targets for the treatment of coronavirus disease

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) quickly spread worldwide, leading coronavirus disease 2019 (COVID-19) to hit pandemic level less than 4 months after the first official cases. Hence, the search for drugs and vaccines that could prevent or treat infections by SARS-CoV-2 began, intending to reduce a possible collapse of health systems. After 2 years, efforts to find therapies to treat COVID-19 continue. However, there is still much to be understood about the virus' pathology. Tools such as transcriptomics have been used to understand the impact of SARS-CoV-2 on different cells isolated from various tissues, leaving datasets in the databases that integrate genes and differentially expressed pathways during SARS-CoV-2 infection. After retrieving transcriptome datasets from different human cells infected with SARS-CoV-2 available in the database, we performed an integrative analysis associated with deep learning algorithms to determine differentially expressed targets mainly after infection. The targets found represented a fructose transporter (GLUT5) and a component of proteasome 26s. These targets were then molecularly modeled, followed by molecular docking that identified potential inhibitors for both structures. Once the inhibition of structures that have the expression increased by the virus can represent a strategy for reducing the viral replication by selecting infected cells, associating these bioinformatics tools, therefore, can be helpful in the screening of molecules being tested for new uses, saving financial resources, time, and making a personalized screening for each infectious disease.

Low perforin expression in CD8+ T lymphocytes during the acute phase of severe SARS-CoV-2 infection predicts long COVID

T cell cytotoxicity plays a major role in antiviral immunity. Anti-SARS-CoV-2 immunity may determine acute disease severity, but also the potential persistence of symptoms (long COVID). We therefore measured the expression of perforin, a cytotoxic mediator, in T cells of patients recently hospitalized for SARS-CoV-2 infection. We recruited 54 volunteers confirmed as being SARS-CoV-2-infected by RT-PCR and admitted to Intensive Care Units (ICUs) or non-ICU, and 29 age- and sex-matched healthy controls (HCs). Amounts of intracellular perforin and granzyme-B, as well as cell surface expression of the degranulation marker CD107A were determined by flow cytometry. The levels of 15 cytokines in plasma were measured by Luminex. The frequency of perforin-positive T4 cells and T8 cells was higher in patients than in HCs (9.9 ± 10.1% versus 4.6 ± 6.4%, p = 0.006 and 46.7 ± 20.6% vs 33.3 ± 18.8%, p = 0.004, respectively). Perforin expression was neither correlated with clinical and biological markers of disease severity nor predictive of death. By contrast, the percentage of perforin-positive T8 cells in the acute phase of the disease predicted the onset of long COVID one year later. A low T8 cytotoxicity in the first days of SARS-CoV-2 infection might favor virus replication and persistence, autoimmunity, and/or reactivation of other viruses such as Epstein-Barr virus or cytomegalovirus, paving the way for long COVID. Under this hypothesis, boosting T cell cytotoxicity during the acute phase of the infection could prevent delayed sequelae.

Combining Deep Phenotyping of Serum Proteomics and Clinical Data via Machine Learning for COVID-19 Biomarker Discovery

The persistence of long-term coronavirus-induced disease 2019 (COVID-19) sequelae demands better insights into its natural history. Therefore, it is crucial to discover the biomarkers of disease outcome to improve clinical practice. In this study, 160 COVID-19 patients were enrolled, of whom 80 had a “non-severe” and 80 had a “severe” outcome. Sera were analyzed by proximity extension assay (PEA) to assess 274 unique proteins associated with inflammation, cardiometabolic, and neurologic diseases. The main clinical and hematochemical data associated with disease outcome were grouped with serological data to form a dataset for the supervised machine learning techniques. We identified nine proteins (i.e., CD200R1, MCP1, MCP3, IL6, LTBP2, MATN3, TRANCE, α2-MRAP, and KIT) that contributed to the correct classification of COVID-19 disease severity when combined with relative neutrophil and lymphocyte counts. By analyzing PEA, clinical and hematochemical data with statistical methods that were able to handle many variables in the presence of a relatively small sample size, we identified nine potential serum biomarkers of a “severe” outcome. Most of these were confirmed by literature data. Importantly, we found three biomarkers associated with central nervous system pathologies and protective factors, which were downregulated in the most severe cases.

Dysregulated Exosomes Result in Suppression of the Immune Response of Pregnant COVID-19 Convalescent Women

A successful pregnancy outcome is dependent on a delicate balance between inflammatory and anti-inflammatory processes throughout the different trimesters. Interruption in this balance can lead to an adverse outcome resulting in pregnancy loss. Since late 2019, the emergence of the new SARS-CoV-2 virus has affected lives worldwide, including pregnant women; therefore, there is an urgent need to address different approaches in relation to prevention, diagnostics, and therapeutics. Early pregnancy is affected by SARS-CoV-2 infection leading to fetal demise. Available evidence also suggests that 90% of pregnant women infected with the SARS-CoV-2 virus seem to be asymptomatic. Nonetheless, it is still unclear how COVID-19 affects exosome production in pregnant women recovered from COVID-19 and how these exosomes regulate the adaptive immune response. In this study, we found several exosomes including CD9, CD31, CD40, CD45, CD41b, CD42a, CD62P, CD69, CD81, CD105, and HLA-DRDPDQ in the plasma of COVID-19-recovered pregnant women were significantly less abundant than the control group. Furthermore, to understand how these exosomes affect the adaptive immune response, we co-cultured the peripheral blood mononuclear cells (PBMCs) from healthy control (HC) pregnant women with exosomes of either Preg-HC or Preg-recovered COVID-19 women. We identified that Preg-recovered COVID-19 women have reduced capacity for the inflammatory cytokine TNF-α from cytotoxic CD8⁺ T cells. In summary, our study highlights that pregnant recovered COVID-19 women have reduced production of several exosomes and possess fewer immunogenic properties. Our study implicates that exosomes can control inflammation and antigen presentation capacity of immune cells, thus limiting the infection in pregnant women.

Liquid Chromatography-Mass Spectrometry Analysis of Peripheral Blood Mononuclear Cells from SARS-CoV-2 Infected Patients

COVID-19 disease is caused by infection with the SARS-CoV-2 virus and is associated with a cytokine storm effect in some patients. This can lead to decreased ability of the host to cope with the infection and result in severe disease outcomes. Here, we present a protocol for isolation of peripheral blood mononuclear cells (PBMCs) from COVID-19 patients followed by liquid chromatography-mass spectrometry (LC-MS) profiling to identify the affected molecules and molecular pathways. It is hoped that this will lead to the identification of potential biomarkers for monitoring the disease as well as treatment responses. This approach could also be used in the study of other respiratory viruses.

Measurement of Mitochondrial Respiration in Cryopreserved Human Peripheral Blood Mononuclear Cells (PBMCs)

Inflammatory diseases caused by infectious agents such as the SARS-CoV-2 virus can lead to impaired reductive-oxidative (REDOX) balance and disrupted mitochondrial function. Peripheral blood mononuclear cells (PBMCs) provide a useful model for studying the effects of inflammatory diseases on mitochondrial function but can be limited by the need to store these cells by cryopreservation prior to assay. Here, we describe a method for improving and determining PBMC viability with normalization of values to number of living cells. The approach can be applied not only to PBMC samples derived from patients with diseases marked by an altered inflammatory response such as viral infections.