Impaired beta-oxidation increases vulnerability to influenza A infection

Carnitine palmitoyl-transferase 1A is potentially involved in bovine herpesvirus 1 productive infection

Bovine herpesvirus 1(BoHV-1) is an important bovine pathogen that causes great economic loss to cattle farms worldwide. The virus-productive infection in bovine kidney (MDBK) cells results in ATP depletion. The mechanisms are not well understood. Mitochondrial fatty acid β-oxidation (FAO) is an important energy source in many tissues with high energy demand. Since carnitine palmitoyl-transferase 1 A (CPT1A) is the rate-limiting enzyme of FAO, we investigated the interactions between virus-productive infection and CPT1A signaling. Here, we found that virus-productive infection at the later stage significantly decreased CPT1A protein levels in all the detected cells, including MDBK, A549, and Neuro-2A cells, differentially altered the accumulation of CPT1A proteins in the nucleus and cytosol, and re-localized the protein in the nucleus. Etomoxir (ETO), an irreversible inhibitor of CPT1A, inhibited viral replication and partially interfered with the ability of BoHV-1 to alter CPT1A accumulation in the nucleus but not in the cytosol. Furthermore, ETO consistently reduced RNA levels of two viral regulatory proteins (bICP0 and bICP22) and protein expression of virion-associated proteins during productive infection, further supporting the important roles of CPT1A signaling in BoHV-1 productive infection. These data, for the first time, suggest that CPT1A is potentially involved in BoHV-1 productive infection.

Systemic perturbations in amino acids/amino acid derivatives and tryptophan pathway metabolites associated with murine influenza A virus infection

BACKGROUND

Influenza A virus (IAV) is the only influenza virus causing flu pandemics (i.e., global epidemics of flu disease). Influenza (the flu) is a highly contagious disease that can be deadly, especially in high-risk groups. Worldwide, these annual epidemics are estimated to result in about 3 to 5 million cases of severe illness and in about 290,000 to 650,000 respiratory deaths. We intend to reveal the effect of IAV infection on the host's metabolism, immune response, and neurotoxicity by using a mouse IAV infection model.

METHODS

51 metabolites of murine blood plasma (33 amino acids/amino acid derivatives (AADs) and 18 metabolites of the tryptophan pathway) were analyzed by using Ultra-High-Performance Liquid Chromatography-Mass Spectrometry with Electrospray Ionization at the acute (7 days post-infection (dpi)), resolution (14 dpi), and recovery (21 dpi) stages of the virus infection in comparison with controls.

RESULTS

Among the 33 biogenic amino acids/AADs, the levels of five amino acids/AADs (1-methylhistidine, 5-oxoproline, α-aminobutyric acid, glutamine, and taurine) increased by 7 dpi, whereas the levels of ten amino acids/AADs (4-hydroxyproline, alanine, arginine, asparagine, cysteine, citrulline, glycine, methionine, proline, and tyrosine) decreased. By 14 dpi, the levels of one AAD (3-methylhistidine) increased, whereas the levels of five amino acids/AADs (α-aminobutyric acid, aminoadipic acid, methionine, threonine, valine) decreased. Among the 18 metabolites from the tryptophan pathway, the levels of kynurenine, quinolinic acid, hydroxykynurenine increased by 7 dpi, whereas the levels of indole-3-acetic acid and nicotinamide riboside decreased.

CONCLUSIONS

Our data may facilitate understanding the molecular mechanisms of host responses to IAV infection and provide a basis for discovering potential new mechanistic, diagnostic, and prognostic biomarkers and therapeutic targets for IAV infection.

Treating Insulin Resistance with Intermittent Personalized Nutrition to Sustain Metabolic Health and Functioning Immune System for Risk Reduction of Viral Diseases Especially COVID-19 and Long-COVID

The Covid-19 pandemic has provided new and strong evidence for poor outcomes of viral infection in patients with poor metabolic health. Insulin resistance is at the root of many metabolic conditions and a key driver of their progression as it promotes ineffectual inflammation whilst impairing immune functions. In a vicious circle, insulin resistance facilitates SARS-CoV-2 infection, whilst infection drives insulin resistance. We discuss the underlying mechanisms and explore ways to improve metabolic health and prevent insulin resistance through early detection and targeted nutritional interventions. With proven efficacy in prediabetes, type 2 diabetes, and their cardiovascular and organ complications, as much as non-alcoholic liver disease, we argue to extend such approaches to ensure resilience to the current pandemic and viral challenges beyond.

Spatial Metabolomics Reveals Localized Impact of Influenza Virus Infection on the Lung Tissue Metabolome

The influenza virus (IAV) is a major cause of respiratory disease, with significant infection increases in pandemic years. Vaccines are a mainstay of IAV prevention but are complicated by IAV’s vast strain diversity and manufacturing and vaccine uptake limitations. While antivirals may be used for treatment of IAV, they are most effective in early stages of the infection, and several virus strains have become drug resistant. Therefore, there is a need for advances in IAV treatment, especially host-directed therapeutics. Given the spatial dynamics of IAV infection and the relationship between viral spatial distribution and disease severity, a spatial approach is necessary to expand our understanding of IAV pathogenesis. We used spatial metabolomics to address this issue. Spatial metabolomics combines liquid chromatography-tandem mass spectrometry of metabolites extracted from systematic organ sections, 3D models, and computational techniques to develop spatial models of metabolite location and their role in organ function and disease pathogenesis. In this project, we analyzed serum and systematically sectioned lung tissue samples from uninfected or infected mice. Spatial mapping of sites of metabolic perturbations revealed significantly lower metabolic perturbation in the trachea compared to other lung tissue sites. Using random forest machine learning, we identified metabolites that responded differently in each lung position based on infection, including specific amino acids, lipids and lipid-like molecules, and nucleosides. These results support the implementation of spatial metabolomics to understand metabolic changes upon respiratory virus infection.

IMPORTANCE The influenza virus is a major health concern. Over 1 billion people become infected annually despite the wide distribution of vaccines, and antiviral agents are insufficient to address current clinical needs. In this study, we used spatial metabolomics to understand changes in the lung and serum metabolome of mice infected with influenza A virus compared to uninfected controls. We determined metabolites altered by infection in specific lung tissue sites and distinguished metabolites perturbed by infection between lung tissue and serum samples. Our findings highlight the utility of a spatial approach to understanding the intersection between the lung metabolome, viral infection, and disease severity. Ultimately, this approach will expand our understanding of respiratory disease pathogenesis.

Metabolites involved in purine degradation, insulin resistance, and fatty acid oxidation are associated with prediction of Gestational diabetes in plasma

INTRODUCTION

Gestational diabetes mellitus (GDM) significantly increases maternal and fetal health risks, but factors predictive of GDM are poorly understood.

OBJECTIVES

Plasma metabolomics analyses were conducted in early pregnancy to identify potential metabolites associated with prediction of GDM.

METHODS

Sixty-eight pregnant women with overweight/obesity from a clinical trial of a lifestyle intervention were included. Participants who developed GDM (n = 34; GDM group) were matched on treatment group, age, body mass index, and ethnicity with those who did not develop GDM (n = 34; Non-GDM group). Blood draws were completed early in pregnancy (10-16 weeks). Plasma samples were analyzed by UPLC-MS using three metabolomics assays.

RESULTS

One hundred thirty moieties were identified. Thirteen metabolites including pyrimidine/purine derivatives involved in uric acid metabolism, carboxylic acids, fatty acylcarnitines, and sphingomyelins (SM) were different when comparing the GDM vs. the Non-GDM groups (p < 0.05). The most significant differences were elevations in the metabolites' hypoxanthine, xanthine and alpha-hydroxybutyrate (p < 0.002, adjusted p < 0.02) in GDM patients. A panel consisting of four metabolites: SM 14:0, hypoxanthine, alpha-hydroxybutyrate, and xanthine presented the highest diagnostic accuracy with an AUC = 0.833 (95% CI: 0.572686-0.893946), classifying as a "very good panel".

CONCLUSION

Plasma metabolites mainly involved in purine degradation, insulin resistance, and fatty acid oxidation, were altered in early pregnancy in connection with subsequent GDM development.