Tryptophan Metabolism and COVID-19-Induced Skeletal Muscle Damage: Is ACE2 a Key Regulator?

Significance of nitrosative stress and glycoxidation products in the diagnosis of COVID-19

Nitrosative stress promotes protein glycoxidation, and both processes can occur during an infection with the SARS-CoV-2 virus. Therefore, the aim of this study was to assess selected nitrosative stress parameters and protein glycoxidation products in COVID-19 patients and convalescents relative to healthy subjects, including in reference to the severity of COVID-19 symptoms. The diagnostic utility of nitrosative stress and protein glycoxidation biomarkers was also evaluated in COVID-19 patients. The study involved 218 patients with COVID-19, 69 convalescents, and 48 healthy subjects. Nitrosative stress parameters (NO, S-nitrosothiols, nitrotyrosine) and protein glycoxidation products (tryptophan, kynurenine, N-formylkynurenine, dityrosine, AGEs) were measured in the blood plasma or serum with the use of colorimetric/fluorometric methods. The levels of NO (p = 0.0480), S-nitrosothiols (p = 0.0004), nitrotyrosine (p = 0.0175), kynurenine (p < 0.0001), N-formylkynurenine (p < 0.0001), dityrosine (p < 0.0001), and AGEs (p < 0.0001) were significantly higher, whereas tryptophan fluorescence was significantly (p < 0.0001) lower in COVID-19 patients than in the control group. Significant differences in the analyzed parameters were observed in different stages of COVID-19. In turn, the concentrations of kynurenine (p < 0.0001), N-formylkynurenine (p < 0.0001), dityrosine (p < 0.0001), and AGEs (p < 0.0001) were significantly higher, whereas tryptophan levels were significantly (p < 0.0001) lower in convalescents than in healthy controls. The ROC analysis revealed that protein glycoxidation products can be useful for diagnosing infections with the SARS-CoV-2 virus because they differentiate COVID-19 patients (KN: sensitivity-91.20%, specificity-92.00%; NFK: sensitivity-92.37%, specificity-92.00%; AGEs: sensitivity-99,02%, specificity-100%) and convalescents (KN: sensitivity-82.22%, specificity-84.00%; NFK: sensitivity-82,86%, specificity-86,00%; DT: sensitivity-100%, specificity-100%; AGE: sensitivity-100%, specificity-100%) from healthy subjects with high sensitivity and specificity. Nitrosative stress and protein glycoxidation are intensified both during and after an infection with the SARS-CoV-2 virus. The levels of redox biomarkers fluctuate in different stages of the disease. Circulating biomarkers of nitrosative stress/protein glycoxidation have potential diagnostic utility in both COVID-19 patients and convalescents.

Integrative Molecular Structure Elucidation and Construction of an Extended Metabolic Pathway Associated with an Ancient Innate Immune Response in COVID-19 Patients

We present compelling evidence for the existence of an extended innate viperin-dependent pathway, which provides crucial evidence for an adaptive response to viral agents, such as SARS-CoV-2. We show the in vivo biosynthesis of a family of novel endogenous cytosine metabolites with potential antiviral activities. Two-dimensional nuclear magnetic resonance (NMR) spectroscopy revealed a characteristic spin-system motif, indicating the presence of an extended panel of urinary metabolites during the acute viral replication phase. Mass spectrometry additionally enabled the characterization and quantification of the most abundant serum metabolites, showing the potential diagnostic value of the compounds for viral infections. In total, we unveiled ten nucleoside (cytosine- and uracil-based) analogue structures, eight of which were previously unknown in humans allowing us to propose a new extended viperin pathway for the innate production of antiviral compounds. The molecular structures of the nucleoside analogues and their correlation with an array of serum cytokines, including IFN-α2, IFN-γ, and IL-10, suggest an association with the viperin enzyme contributing to an ancient endogenous innate immune defense mechanism against viral infection.

Potential Beneficial Effects of Naringin and Naringenin on Long COVID-A Review of the Literature

Coronavirus disease 2019 (COVID-19) caused a severe epidemic due to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Recent studies have found that patients do not completely recover from acute infections, but instead, suffer from a variety of post-acute sequelae of SARS-CoV-2 infection, known as long COVID. The effects of long COVID can be far-reaching, with a duration of up to six months and a range of symptoms such as cognitive dysfunction, immune dysregulation, microbiota dysbiosis, myalgic encephalomyelitis/chronic fatigue syndrome, myocarditis, pulmonary fibrosis, cough, diabetes, pain, reproductive dysfunction, and thrombus formation. However, recent studies have shown that naringenin and naringin have palliative effects on various COVID-19 sequelae. Flavonoids such as naringin and naringenin, commonly found in fruits and vegetables, have various positive effects, including reducing inflammation, preventing viral infections, and providing antioxidants. This article discusses the molecular mechanisms and clinical effects of naringin and naringenin on treating the above diseases. It proposes them as potential drugs for the treatment of long COVID, and it can be inferred that naringin and naringenin exhibit potential as extended long COVID medications, in the future likely serving as nutraceuticals or clinical supplements for the comprehensive alleviation of the various manifestations of COVID-19 complications.

The metaproteome of the gut microbiota in pediatric patients affected by COVID-19

Introduction

The gut microbiota (GM) play a significant role in the infectivity and severity of COVID-19 infection. However, the available literature primarily focuses on adult patients and it is known that the microbiota undergoes changes throughout the lifespan, with significant alterations occurring during infancy and subsequently stabilizing during adulthood. Moreover, children have exhibited milder symptoms of COVID-19 disease, which has been associated with the abundance of certain protective bacteria. Here, we examine the metaproteome of pediatric patients to uncover the biological mechanisms that underlie this protective effect of the GM.

Methods

We performed nanoliquid chromatography coupled with tandem mass spectrometry on a high resolution analytical platform, resulting in label free quantification of bacterial protein groups (PGs), along with functional annotations via COG and KEGG databases by MetaLab-MAG. Additionally, taxonomic assignment was possible through the use of the lowest common ancestor algorithm provided by Unipept software.

Results

A COVID-19 GM functional dissimilarity respect to healthy subjects was identified by univariate analysis. The alteration in COVID-19 GM function is primarily based on bacterial pathways that predominantly involve metabolic processes, such as those related to tryptophan, butanoate, fatty acid, and bile acid biosynthesis, as well as antibiotic resistance and virulence.

Discussion

These findings highlight the mechanisms by which the pediatric GM could contribute to protection against the more severe manifestations of the disease in children. Uncovering these mechanisms can, therefore, have important implications in the discovery of novel adjuvant therapies for severe COVID-19.

A comparative NMR-based metabolomics study of lung parenchyma of severe COVID-19 patients

COVID-19 was the most significant infectious-agent-related cause of death in the 2020-2021 period. On average, over 60% of those admitted to ICU facilities with this disease died across the globe. In severe cases, COVID-19 leads to respiratory and systemic compromise, including pneumonia-like symptoms, acute respiratory distress syndrome, and multiorgan failure. While the upper respiratory tract and lungs are the principal sites of infection and injury, most studies on the metabolic signatures in COVID-19 patients have been carried out on serum and plasma samples. In this report we attempt to characterize the metabolome of lung parenchyma extracts from fatal COVID-19 cases and compare them with that from other respiratory diseases. Our findings indicate that the metabolomic profiles from fatal COVID-19 and non-COVID-19 cases are markedly different, with the former being the result of increased lactate and amino acid metabolism, altered energy pathways, oxidative stress, and inflammatory response. Overall, these findings provide additional insights into the pathophysiology of COVID-19 that could lead to the development of targeted therapies for the treatment of severe cases of the disease, and further highlight the potential of metabolomic approaches in COVID-19 research.

Developing A Baseline Metabolomic Signature Associated with COVID-19 Severity: Insights from Prospective Trials Encompassing 13 U.S. Centers

Metabolic disease is a significant risk factor for severe COVID-19 infection, but the contributing pathways are not yet fully elucidated. Using data from two randomized controlled trials across 13 U.S. academic centers, our goal was to characterize metabolic features that predict severe COVID-19 and define a novel baseline metabolomic signature. Individuals (n = 133) were dichotomized as having mild or moderate/severe COVID-19 disease based on the WHO ordinal scale. Blood samples were analyzed using the Biocrates platform, providing 630 targeted metabolites for analysis. Resampling techniques and machine learning models were used to determine metabolomic features associated with severe disease. Ingenuity Pathway Analysis (IPA) was used for functional enrichment analysis. To aid in clinical decision making, we created baseline metabolomics signatures of low-correlated molecules. Multivariable logistic regression models were fit to associate these signatures with severe disease on training data. A three-metabolite signature, lysophosphatidylcholine a C17:0, dihydroceramide (d18:0/24:1), and triacylglyceride (20:4_36:4), resulted in the best discrimination performance with an average test AUROC of 0.978 and F1 score of 0.942. Pathways related to amino acids were significantly enriched from the IPA analyses, and the mitogen-activated protein kinase kinase 5 (MAP2K5) was differentially activated between groups. In conclusion, metabolites related to lipid metabolism efficiently discriminated between mild vs. moderate/severe disease. SDMA and GABA demonstrated the potential to discriminate between these two groups as well. The mitogen-activated protein kinase kinase 5 (MAP2K5) regulator is differentially activated between groups, suggesting further investigation as a potential therapeutic pathway.

Mechanism and potential treatments for gastrointestinal dysfunction in patients with COVID-19

The global coronavirus disease 2019 (COVID-19) has become one of the biggest threats to the world since 2019. The respiratory and gastrointestinal tracts are the main targets for severe acute respiratory syndrome coronavirus 2 infection for they highly express angiotensin-converting enzyme-2 and transmembrane protease serine 2. In patients suffering from COVID-19, gastrointestinal symptoms have ranged from 12% to 61%. Anorexia, nausea and/or vomiting, diarrhea, and abdominal pain are considered to be the main gastrointestinal symptoms of COVID-19. It has been reported that the direct damage of intestinal mucosal epithelial cells, malnutrition, and intestinal flora disorders are involved in COVID-19. However, the underlying mechanisms remain unclear. Thus, in this study, we reviewed and discussed the correlated mechanisms that cause gastrointestinal symptoms in order to help to develop the treatment strategy and build an appropriate guideline for medical workers.

Growth Differentiation Factor 15 (GDF-15) Levels Associate with Lower Survival in Chronic Kidney Disease Patients with COVID-19

A cytokine storm drives the pathogenesis of severe COVID-19 infection and several biomarkers have been linked to mortality. Chronic kidney disease (CKD) emerged as a risk factor for severe COVID-19. We investigated the association between selected biomarkers and mortality in 77 patients hospitalized for COVID-19, and whether they differ in patients with eGFR higher and lower than 45 mL/min. The association between patients’ characteristics, plasma biomarkers and mortality was conducted by univariate logistic regression models and independent predictors of mortality were then used to create a multivariate prediction model through Cox regression. Patients with lower eGFR had a significant increase of GDF-15, CD-25 and RAGE, with higher plasma levels in non-survivors and in patients who needed ventilation. At univariate analysis, low and mid-low GDF-15 quartiles (<4.45 ng/mL) were associated with lower mortality risk, while mid-high and high quartiles (>4.45 ng/mL) were associated with higher mortality risk. Independent association between GDF-15 quartiles and mortality risk was confirmed in the Cox model and adjusted for eGFR, age, fever and dyspnea (HR 2.28, CI 1.53−3.39, p < 0.0001). The strength of the association between GDF-15 quartiles and mortality risk increased in patients with lower compared to higher eGFR (HR 2.53, CI 1.34−4.79 versus HR 1.99, CI 1.17−3.39). Our findings may suggest a further investigation of the effect of GDF-15 signaling pathway inhibition in CKD.

Computational approaches for network-based integrative multi-omics analysis

Advances in omics technologies allow for holistic studies into biological systems. These studies rely on integrative data analysis techniques to obtain a comprehensive view of the dynamics of cellular processes, and molecular mechanisms. Network-based integrative approaches have revolutionized multi-omics analysis by providing the framework to represent interactions between multiple different omics-layers in a graph, which may faithfully reflect the molecular wiring in a cell. Here we review network-based multi-omics/multi-modal integrative analytical approaches. We classify these approaches according to the type of omics data supported, the methods and/or algorithms implemented, their node and/or edge weighting components, and their ability to identify key nodes and subnetworks. We show how these approaches can be used to identify biomarkers, disease subtypes, crosstalk, causality, and molecular drivers of physiological and pathological mechanisms. We provide insight into the most appropriate methods and tools for research questions as showcased around the aetiology and treatment of COVID-19 that can be informed by multi-omics data integration. We conclude with an overview of challenges associated with multi-omics network-based analysis, such as reproducibility, heterogeneity, (biological) interpretability of the results, and we highlight some future directions for network-based integration.