A platelet lipidomics signature in patients with COVID-19.

Ischemic cardiovascular and venous thromboembolic events are a frequent cause of death in severe COVID-19 patients. Platelet activation plays a key role in these complications, however platelet lipidomics have not been studied yet. The aim of our pilot investigation was to perform a preliminary study of platelet lipidomics in COVID-19 patients compared to healthy subjects. Lipid extraction and identification of ultrapurified platelets from eight hospitalized COVID-19 patients and eight age- and sex-matched healthy controls showed a lipidomic pattern almost completely separating COVID-19 patients from healthy controls. In particular, a significant decrease of ether phospholipids and increased levels of ganglioside GM3 were observed in platelets from COVID-19 patients. In conclusion, our study shows for the first time that platelets from COVID-19 patients display a different lipidomics signature distinguishing them from healthy controls, and suggests that altered platelet lipid metabolism may play a role in viral spreading and in the thrombotic complications of COVID-19.

What is the context? Besides respiratory system involvement, venous thromboembolism is a severe complication of COVID-19, largely due to the strong derangement of hemostasis, with platelets playing a central role.Great attention has recently been devoted to lipid alterations in COVID-19, both because viruses by reprogramming cellular lipid metabolism remodel lipid membranes to fuel their replication, and because the COVID-19-associated cytokine storm may affect cell/plasma lipidomic signatures.Lipidomics studies in COVID-19 patients have been performed mainly in plasma and serum.To the best of our knowledge, platelet lipidomics have not been examined despite the central role played by platelets in COVID-19 complications.What is the aim of the study?The aim of our pilot study was to preliminarily explore whether platelet lipidomics is altered in COVID-19 patients compared to age- and sex-matched healthy subjects, analyzing lipidomic profile of ultrapurified platelets.What are the results of our study? Our study shows for the first time that platelets from COVID-19 patients display a different lipidomics signature distinguishing them from healthy controls.Ether phospholipids and, intriguingly, two phytoceramides were lower, while ganglioside GM3 was higher in COVID-19 samples compared to healthy controls.What is the impact?Despite the small number of COVID-19 patients enrolled, recognized as a limitation of our study, we show, for the first time, that platelets from COVID-19 patients present a different lipidomics signature and suggest that altered platelet lipid metabolism may play a significant role in viral spreading and in the thrombotic complications of COVID-19.

Classification of Common Food Lipid Sources Regarding Healthiness Using Advanced Lipidomics: A Four-Arm Crossover Study.

Prospective studies have failed to establish a causal relationship between animal fat intake and cardiovascular diseases in humans. Furthermore, the metabolic effects of different dietary sources remain unknown. In this four-arm crossover study, we investigated the impact of consuming cheese, beef, and pork meat on classic and new cardiovascular risk markers (obtained from lipidomics) in the context of a healthy diet. A total of 33 young healthy volunteers (23 women/10 men) were assigned to one out of four test diets in a Latin square design. Each test diet was consumed for 14 days, with a 2-week washout. Participants received a healthy diet plus Gouda- or Goutaler-type cheeses, pork, or beef meats. Before and after each diet, fasting blood samples were withdrawn. A reduction in total cholesterol and an increase in high density lipoprotein particle size were detected after all diets. Only the pork diet upregulated plasma unsaturated fatty acids and downregulated triglycerides species. Improvements in the lipoprotein profile and upregulation of circulating plasmalogen species were also observed after the pork diet. Our study suggests that, within the context of a healthy diet rich in micronutrients and fiber, the consumption of animal products, in particular pork meat, may not induce deleterious effects, and reducing the intake of animal products should not be regarded as a way of reducing cardiovascular risk in young individuals.

Lipidomic signatures align with inflammatory patterns and outcomes in critical illness.

Alterations in lipid metabolism have the potential to be markers as well as drivers of pathobiology of acute critical illness. Here, we took advantage of the temporal precision offered by trauma as a common cause of critical illness to identify the dynamic patterns in the circulating lipidome in critically ill humans. The major findings include an early loss of all classes of circulating lipids followed by a delayed and selective lipogenesis in patients destined to remain critically ill. The previously reported survival benefit of early thawed plasma administration was associated with preserved lipid levels that related to favorable changes in coagulation and inflammation biomarkers in causal modelling. Phosphatidylethanolamines (PE) were elevated in patients with persistent critical illness and PE levels were prognostic for worse outcomes not only in trauma but also severe COVID-19 patients. Here we show selective rise in systemic PE as a common prognostic feature of critical illness.

Lipidomics Revealed Plasma Phospholipid Profile Differences between Deceased and Recovered COVID-19 Patients.

Thorough understanding of metabolic changes, including lipidome alteration, associated with the development of COVID-19 appears to be crucial, as new types of coronaviruses are still reported. In this study, we analyzed the differences in the plasma phospholipid profiles of the deceased COVID-19 patients, those who recovered and healthy people. Due to identified abnormalities in plasma phospholipid profiles, deceased patients were further divided into two subgroups (D1 and D2). Increased levels of phosphatidylethanolamines (PE), phosphatidylcholines (PC) and phosphatidylserines (PS) were found in the plasma of recovered patients and the majority of deceased patients (first subgroup D1) compared to the control group. However, abundances of all relevant PE, PC and PS species decreased dramatically in the plasma of the second subgroup (D2) of five deceased patients. These patients also had significantly decreased plasma COX-2 activity when compared to the control, in contrast to unchanged and increased COX-2 activity in the plasma of the other deceased patients and recovered patients, respectively. Moreover, these five deceased patients were characterized by abnormally low CRP levels and tremendous increase in LDH levels, which may be the result of other pathophysiological disorders, including disorders of the immune system, liver damage and haemolytic anemia. In addition, an observed trend to decrease the autoantibodies against oxidative modifications of low-density lipoprotein (oLAb) titer in all, especially in deceased patients, indicate systemic oxidative stress and altered immune system that may have prognostic value in COVID-19.

Development of a multiomics model for identification of predictive biomarkers for COVID-19 severity: a retrospective cohort study.

BACKGROUND: COVID-19 is a multi-system disorder with high variability in clinical outcomes among patients who are admitted to hospital. Although some cytokines such as interleukin (IL)-6 are believed to be associated with severity, there are no early biomarkers that can reliably predict patients who are more likely to have adverse outcomes. Thus, it is crucial to discover predictive markers of serious complications. METHODS: In this retrospective cohort study, we analysed samples from 455 participants with COVID-19 who had had a positive SARS-CoV-2 RT-PCR result between April 14, 2020, and Dec 1, 2020 and who had visited one of three Mayo Clinic sites in the USA (Minnesota, Arizona, or Florida) in the same period. These participants were assigned to three subgroups depending on disease severity as defined by the WHO ordinal scale of clinical improvement (outpatient, severe, or critical). Our control cohort comprised of 182 anonymised age-matched and sex-matched plasma samples that were available from the Mayo Clinic Biorepository and banked before the COVID-19 pandemic. We did a deep profiling of circulatory cytokines and other proteins, lipids, and metabolites from both cohorts. Most patient samples were collected before, or around the time of, hospital admission, representing ideal samples for predictive biomarker discovery. We used proximity extension assays to quantify cytokines and circulatory proteins and tandem mass spectrometry to measure lipids and metabolites. Biomarker discovery was done by applying an AutoGluon-tabular classifier to a multiomics dataset, producing a stacked ensemble of cutting-edge machine learning algorithms. Global proteomics and glycoproteomics on a subset of patient samples with matched pre-COVID-19 plasma samples was also done. FINDINGS: We quantified 1463 cytokines and circulatory proteins, along with 902 lipids and 1018 metabolites. By developing a machine-learning-based prediction model, a set of 102 biomarkers, which predicted severe and clinical COVID-19 outcomes better than the traditional set of cytokines, were discovered. These predictive biomarkers included several novel cytokines and other proteins, lipids, and metabolites. For example, altered amounts of C-type lectin domain family 6 member A (CLEC6A), ether phosphatidylethanolamine (P-18:1/18:1), and 2-hydroxydecanoate, as reported here, have not previously been associated with severity in COVID-19. Patient samples with matched pre-COVID-19 plasma samples showed similar trends in muti-omics signatures along with differences in glycoproteomics profile. INTERPRETATION: A multiomic molecular signature in the plasma of patients with COVID-19 before being admitted to hospital can be exploited to predict a more severe course of disease. Machine learning approaches can be applied to highly complex and multidimensional profiling data to reveal novel signatures of clinical use. The absence of validation in an independent cohort remains a major limitation of the study. FUNDING: Eric and Wendy Schmidt.

Untargeted lipidomics reveals specific lipid profiles in COVID-19 patients with different severity from Campania region (Italy).

COVID-19 infection evokes various systemic alterations that push patients not only towards severe acute respiratory syndrome but causes an important metabolic dysregulation with following multi-organ alteration and potentially poor outcome. To discover novel potential biomarkers able to predict disease's severity and patient's outcome, in this study we applied untargeted lipidomics, by a reversed phase ultra-high performance liquid chromatography-trapped ion mobility mass spectrometry platform (RP-UHPLC-TIMS-MS), on blood samples collected at hospital admission in an Italian cohort of COVID-19 patients (45 mild, 54 severe, 21 controls). In a subset of patients, we also collected a second blood sample in correspondence of clinical phenotype modification (longitudinal population). Plasma lipid profiles revealed several lipids significantly modified in COVID-19 patients with respect to controls and able to discern between mild and severe clinical phenotype. Severe patients were characterized by a progressive decrease in the levels of LPCs, LPC-Os, PC-Os, and, on the contrary, an increase in overall TGs, PEs, and Ceramides. A machine learning model was built by using both the entire dataset and with a restricted lipid panel dataset, delivering comparable results in predicting severity (AUC= 0.777, CI: 0.639-0.904) and outcome (AUC= 0.789, CI: 0.658-0.910). Finally, re-building the model with 25 longitudinal (t1) samples, this resulted in 21 patients correctly classified. In conclusion, this study highlights specific lipid profiles that could be used monitor the possible trajectory of COVID-19 patients at hospital admission, which could be used in targeted approaches.

The Platelet Lipidome Is Altered in Patients with COVID-19 and Correlates with Platelet Reactivity.

BACKGROUND: Activated platelets have been implicated in the proinflammatory and prothrombotic phenotype of coronavirus disease 2019 (COVID-19). While it is increasingly recognized that lipids have important structural and signaling roles in platelets, the lipidomic landscape of platelets during infection has remained unexplored. OBJECTIVE: To investigate the platelet lipidome of patients hospitalized for COVID-19. METHODS: We performed untargeted lipidomics in platelets of 25 patients hospitalized for COVID-19 and 23 noninfectious controls with similar age and sex characteristics, and with comparable comorbidities. RESULTS: Twenty-five percent of the 1,650 annotated lipids were significantly different between the groups. The significantly altered part of the platelet lipidome mostly comprised lipids that were less abundant in patients with COVID-19 (20.4% down, 4.6% up, 75% unchanged). Platelets from COVID-19 patients showed decreased levels of membrane plasmalogens, and a distinct decrease of long-chain, unsaturated triacylglycerols. Conversely, platelets from patients with COVID-19 displayed class-wide higher abundances of bis(monoacylglycero)phosphate and its biosynthetic precursor lysophosphatidylglycerol. Levels of these classes positively correlated with ex vivo platelet reactivity-as measured by P-selectin expression after PAR1 activation-irrespective of disease state. CONCLUSION: Taken together, this investigation provides the first exploration of the profound impact of infection on the human platelet lipidome, and reveals associations between the lipid composition of platelets and their reactivity. These results warrant further lipidomic research in other infections and disease states involving platelet pathophysiology.

Machine learning and semi-targeted lipidomics identify distinct serum lipid signatures in hospitalized COVID-19-positive and COVID-19-negative patients.

BACKGROUND: Lipids are involved in the interaction between viral infection and the host metabolic and immunological responses. Several studies comparing the lipidome of COVID-19-positive hospitalized patients vs. healthy subjects have already been reported. It is largely unknown, however, whether these differences are specific to this disease. The present study compared the lipidomic signature of hospitalized COVID-19-positive patients with that of healthy subjects, as well as with COVID-19-negative patients hospitalized for other infectious/inflammatory diseases. METHODS: We analyzed the lipidomic signature of 126 COVID-19-positive patients, 45 COVID-19-negative patients hospitalized with other infectious/inflammatory diseases and 50 healthy volunteers. A semi-targeted lipidomics analysis was performed using liquid chromatography coupled to mass spectrometry. Two-hundred and eighty-three lipid species were identified and quantified. Results were interpreted by machine learning tools. RESULTS: We identified acylcarnitines, lysophosphatidylethanolamines, arachidonic acid and oxylipins as the most altered species in COVID-19-positive patients compared to healthy volunteers. However, we found similar alterations in COVID-19-negative patients who had other causes of inflammation. Conversely, lysophosphatidylcholine 22:6-sn2, phosphatidylcholine 36:1 and secondary bile acids were the parameters that had the greatest capacity to discriminate between COVID-19-positive and COVID-19-negative patients. CONCLUSION: This study shows that COVID-19 infection shares many lipid alterations with other infectious/inflammatory diseases, and which differentiate them from the healthy population. The most notable alterations were observed in oxylipins, while alterations in bile acids and glycerophospholipis best distinguished between COVID-19-positive and COVID-19-negative patients. Our results highlight the value of integrating lipidomics with machine learning algorithms to explore the pathophysiology of COVID-19 and, consequently, improve clinical decision making.

High-Fat High-Sugar Diet-Induced Changes in the Lipid Metabolism Are Associated with Mildly Increased COVID-19 Severity and Delayed Recovery in the Syrian Hamster.

Pre-existing comorbidities such as obesity or metabolic diseases can adversely affect the clinical outcome of COVID-19. Chronic metabolic disorders are globally on the rise and often a consequence of an unhealthy diet, referred to as a Western Diet. For the first time in the Syrian hamster model, we demonstrate the detrimental impact of a continuous high-fat high-sugar diet on COVID-19 outcome. We observed increased weight loss and lung pathology, such as exudate, vasculitis, hemorrhage, fibrin, and edema, delayed viral clearance and functional lung recovery, and prolonged viral shedding. This was accompanied by an altered, but not significantly different, systemic IL-10 and IL-6 profile, as well as a dysregulated serum lipid response dominated by polyunsaturated fatty acid-containing phosphatidylethanolamine, partially recapitulating cytokine and lipid responses associated with severe human COVID-19. Our data support the hamster model for testing restrictive or targeted diets and immunomodulatory therapies to mediate the adverse effects of metabolic disease on COVID-19.

Link between serum lipid signature and prognostic factors in COVID-19 patients.

Although the serum lipidome is markedly affected by COVID-19, two unresolved issues remain: how the severity of the disease affects the level and the composition of serum lipids and whether serum lipidome analysis may identify specific lipids impairment linked to the patients' outcome. Sera from 49 COVID-19 patients were analyzed by untargeted lipidomics. Patients were clustered according to: inflammation (C-reactive protein), hypoxia (Horowitz Index), coagulation state (D-dimer), kidney function (creatinine) and age. COVID-19 patients exhibited remarkable and distinctive dyslipidemia for each prognostic factor associated with reduced defense against oxidative stress. When patients were clustered by outcome (7 days), a peculiar lipidome signature was detected with an overall increase of 29 lipid species, including-among others-four ceramide and three sulfatide species, univocally related to this analysis. Considering the lipids that were affected by all the prognostic factors, we found one sphingomyelin related to inflammation and viral infection of the respiratory tract and two sphingomyelins, that are independently related to patients' age, and they appear as candidate biomarkers to monitor disease progression and severity. Although preliminary and needing validation, this report pioneers the translation of lipidome signatures to link the effects of five critical clinical prognostic factors with the patients' outcomes.

ATP/IL-33-triggered hyperactivation of mast cells results in an amplified production of pro-inflammatory cytokines and eicosanoids.

IL-33 and ATP are alarmins, which are released upon damage of cellular barriers or are actively secreted upon cell stress. Due to high-density expression of the IL-33 receptor T1/ST2 (IL-33R), and the ATP receptor P2X7, mast cells (MCs) are one of the first highly sensitive sentinels recognizing released IL-33 or ATP in damaged peripheral tissues. Whereas IL-33 induces the MyD88-dependent activation of the TAK1-IKK2-NF-κB signalling, ATP induces the Ca2+ -dependent activation of NFAT. Thereby, each signal alone only induces a moderate production of pro-inflammatory cytokines and lipid mediators (LMs). However, MCs, which simultaneously sense (co-sensing) IL-33 and ATP, display an enhanced and prolonged activation of the TAK1-IKK2-NF-κB signalling pathway. This resulted in a massive production of pro-inflammatory cytokines such as IL-2, IL-4, IL-6 and GM-CSF as well as of arachidonic acid-derived cyclooxygenase (COX)-mediated pro-inflammatory prostaglandins (PGs) and thromboxanes (TXs), hallmarks of strong MC activation. Collectively, these data show that co-sensing of ATP and IL-33 results in hyperactivation of MCs, which resembles to MC activation induced by IgE-mediated crosslinking of the FcεRI. Therefore, the IL-33/IL-33R and/or the ATP/P2X7 signalling axis are attractive targets for therapeutical intervention of diseases associated with the loss of integrity of cellular barriers such as allergic and infectious respiratory reactions.

Uneven metabolic and lipidomic profiles in recovered COVID-19 patients as investigated by plasma NMR metabolomics.

COVID-19 is a systemic infectious disease that may affect many organs, accompanied by a measurable metabolic dysregulation. The disease is also associated with significant mortality, particularly among the elderly, patients with comorbidities, and solid organ transplant recipients. Yet, the largest segment of the patient population is asymptomatic, and most other patients develop mild to moderate symptoms after SARS-CoV-2 infection. Here, we have used NMR metabolomics to characterize plasma samples from a cohort of the abovementioned group of COVID-19 patients (n = 69), between 3 and 10 months after diagnosis, and compared them with a set of reference samples from individuals never infected by the virus (n = 71). Our results indicate that half of the patient population show abnormal metabolism including porphyrin levels and altered lipoprotein profiles six months after the infection, while the other half show little molecular record of the disease. Remarkably, most of these patients are asymptomatic or mild COVID-19 patients, and we hypothesize that this is due to a metabolic reflection of the immune response stress.

Severity of COVID-19 Patients Predicted by Serum Sphingolipids Signature.

The reason behind the high inter-individual variability in response to SARS-CoV-2 infection and patient's outcome is poorly understood. The present study targets the sphingolipid profile of twenty-four healthy controls and fifty-nine COVID-19 patients with different disease severity. Sera were analyzed by untargeted and targeted mass spectrometry and ELISA. Results indicated a progressive increase in dihydrosphingosine, dihydroceramides, ceramides, sphingosine, and a decrease in sphingosine-1-phosphate. These changes are associated with a serine palmitoyltransferase long chain base subunit 1 (SPTLC1) increase in relation to COVID-19 severity. Severe patients showed a decrease in sphingomyelins and a high level of acid sphingomyelinase (aSMase) that influences monosialodihexosyl ganglioside (GM3) C16:0 levels. Critical patients are characterized by high levels of dihydrosphingosine and dihydroceramide but not of glycosphingolipids. In severe and critical patients, unbalanced lipid metabolism induces lipid raft remodeling, leads to cell apoptosis and immunoescape, suggesting active sphingolipid participation in viral infection. Furthermore, results indicated that the sphingolipid and glycosphingolipid metabolic rewiring promoted by aSMase and GM3 is age-dependent but also characteristic of severe and critical patients influencing prognosis and increasing viral load. AUCs calculated from ROC curves indicated ceramides C16:0, C18:0, C24:1, sphingosine and SPTLC1 as putative biomarkers of disease evolution.

The trans-omics landscape of COVID-19.

The outbreak of coronavirus disease 2019 (COVID-19) is a global health emergency. Various omics results have been reported for COVID-19, but the molecular hallmarks of COVID-19, especially in those patients without comorbidities, have not been fully investigated. Here we collect blood samples from 231 COVID-19 patients, prefiltered to exclude those with selected comorbidities, yet with symptoms ranging from asymptomatic to critically ill. Using integrative analysis of genomic, transcriptomic, proteomic, metabolomic and lipidomic profiles, we report a trans-omics landscape for COVID-19. Our analyses find neutrophils heterogeneity between asymptomatic and critically ill patients. Meanwhile, neutrophils over-activation, arginine depletion and tryptophan metabolites accumulation correlate with T cell dysfunction in critical patients. Our multi-omics data and characterization of peripheral blood from COVID-19 patients may thus help provide clues regarding pathophysiology of and potential therapeutic strategies for COVID-19.

A lipidomic view of SARS-CoV-2.

The global pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which started in late 2019, has caused huge social and economic losses. A growing number of investigators are focusing on understanding the interaction of SARS-CoV-2 with host cellular processes to find therapeutic approaches. New data suggest that lipid metabolism may play a significant role in regulating the response of immune cells like macrophages to viral infection, thereby affecting the outcome of the disease. Therefore, understanding the role of lipid metabolism could help develop new therapeutic approaches to mitigate the social and economic cost of coronavirus disease 2019 (COVID-19).

Tissue Lipidomic Alterations Induced by Prolonged Dexamethasone Treatment.

Dexamethasone is a synthetic glucocorticoid medication vastly used to treat abnormal immune responses and inflammation. Although the medication is well-established in the medical community, the prolonged treatment with high dosages of dexamethasone may lead to severe adverse effects through mechanisms that are not yet well-known. Lipids are a large class of hydrophobic molecules involved in energy storage, signaling, modulation of gene expression, and membranes. Hence, untargeted lipidomics may help unravel the biochemical alterations following prolonged treatment with high dosages of dexamethasone. We performed comprehensive lipidomic analyses of brain, heart, kidney, liver, and muscle samples obtained from rats that were treated with intramuscular injections of dexamethasone for 14 weeks compared to healthy controls. The employed methodology and statistical analysis showed that phosphatidic acids, glycerophospholipids, plasmalogens, and fatty acids are deeply affected by prolonged use of the medication. Brain tissue was only mildly affected, but skeletal muscle showed a strong accumulation of lipids that may be correlated with alterations in the energy metabolism, myopathy, and oxidative processes. This work provides new insights into the mechanisms of action and adverse effects for one of the most commonly prescribed class of drugs in the world.

Plasma Markers of Disrupted Gut Permeability in Severe COVID-19 Patients.

A disruption of the crosstalk between the gut and the lung has been implicated as a driver of severity during respiratory-related diseases. Lung injury causes systemic inflammation, which disrupts gut barrier integrity, increasing the permeability to gut microbes and their products. This exacerbates inflammation, resulting in positive feedback. We aimed to test whether severe Coronavirus disease 2019 (COVID-19) is associated with markers of disrupted gut permeability. We applied a multi-omic systems biology approach to analyze plasma samples from COVID-19 patients with varying disease severity and SARS-CoV-2 negative controls. We investigated the potential links between plasma markers of gut barrier integrity, microbial translocation, systemic inflammation, metabolome, lipidome, and glycome, and COVID-19 severity. We found that severe COVID-19 is associated with high levels of markers of tight junction permeability and translocation of bacterial and fungal products into the blood. These markers of disrupted intestinal barrier integrity and microbial translocation correlate strongly with higher levels of markers of systemic inflammation and immune activation, lower levels of markers of intestinal function, disrupted plasma metabolome and glycome, and higher mortality rate. Our study highlights an underappreciated factor with significant clinical implications, disruption in gut functions, as a potential force that may contribute to COVID-19 severity.

A multi-omics investigation of the composition and function of extracellular vesicles along the temporal trajectory of COVID-19.

Exosomes represent a subtype of extracellular vesicle that is released through retrograde transport and fusion of multivesicular bodies with the plasma membrane1. Although no perfect methodologies currently exist for the high-throughput, unbiased isolation of pure plasma exosomes2,3, investigation of exosome-enriched plasma fractions of extracellular vesicles can confer a glimpse into the endocytic pathway on a systems level. Here we conduct high-coverage lipidomics with an emphasis on sterols and oxysterols, and proteomic analyses of exosome-enriched extracellular vesicles (EVs hereafter) from patients at different temporal stages of COVID-19, including the presymptomatic, hyperinflammatory, resolution and convalescent phases. Our study highlights dysregulated raft lipid metabolism that underlies changes in EV lipid membrane anisotropy that alter the exosomal localization of presenilin-1 (PS-1) in the hyperinflammatory phase. We also show in vitro that EVs from different temporal phases trigger distinct metabolic and transcriptional responses in recipient cells, including in alveolar epithelial cells, which denote the primary site of infection, and liver hepatocytes, which represent a distal secondary site. In comparison to the hyperinflammatory phase, EVs from the resolution phase induce opposing effects on eukaryotic translation and Notch signalling. Our results provide insights into cellular lipid metabolism and inter-tissue crosstalk at different stages of COVID-19 and are a resource to increase our understanding of metabolic dysregulation in COVID-19.

Differential role of sphingomyelin in influenza virus, rhinovirus and SARS-CoV-2 infection of Calu-3 cells.

Host cell lipids play a pivotal role in the pathogenesis of respiratory virus infection. However, a direct comparison of the lipidomic profile of influenza virus and rhinovirus infections is lacking. In this study, we first compared the lipid profile of influenza virus and rhinovirus infection in a bronchial epithelial cell line. Most lipid features were downregulated for both influenza virus and rhinovirus, especially for the sphingomyelin features. Pathway analysis showed that sphingolipid metabolism was the most perturbed pathway. Functional study showed that bacterial sphingomyelinase suppressed influenza virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication, but promoted rhinovirus replication. These findings suggest that sphingomyelin pathway can be a potential target for antiviral therapy, but should be carefully evaluated as it has opposite effects on different respiratory viruses. Furthermore, the differential effect of sphingomyelinase on rhinovirus and influenza virus may explain the interference between rhinovirus and influenza virus infection.