Introduction: It is widely but erroneously believed that drugs get into cells by passing through the phospholipid bilayer portion of the plasma and other membranes. Much evidence shows, however, that this is not the case, and that drugs cross biomembranes by hitchhiking on transporters for other natural molecules to which these drugs are structurally similar. Untargeted metabolomics can provide a method for determining the differential uptake of such metabolites. Objectives: Blood serum contains many thousands of molecules and provides a convenient source of biologically relevant metabolites. Our objective was to detect and identify metabolites present in serum, but to also establish a method capable of measure their uptake and secretion by different cell lines. Methods: We develop an untargeted LC-MS/MS method to detect a broad range of compounds present in human serum. We apply this to the analysis of the time course of the uptake and secretion of metabolites in serum by several human cell lines, by analysing changes in the serum that represents the extracellular phase (the ‘exometabolome’ or metabolic footprint). Results: Our method measures some 4000–5000 metabolic features in both positive and negative electrospray ionisation modes. We show that the metabolic footprints of different cell lines differ greatly from each other. Conclusion: Our new, 15-min untargeted metabolome method allows for the robust and convenient measurement of differences in the uptake of serum compounds by cell lines following incubation in serum. This will enable future research to study these differences in multiple cell lines that will relate this to transporter expression, thereby advancing our knowledge of transporter substrates, both natural and xenobiotic compounds.

We have previously shown that the hepatitis C virus (HCV) E1E2 envelope glycoprotein can regulate HIV-1 long-terminal repeat (LTR) activity through disruption to NF-κB activation. This response is associated with upregulation of the endoplasmic reticulum (ER) stress response pathway. Here, we demonstrate that the SARS-CoV-2 S, M, and E but not the N structural protein can perform similar downmodulation of HIV-1 LTR activation, and in a dose-dependent manner, in both HEK293 and lung BEAS-2B cell lines. This effect is highest with the SARS-CoV-2 Wuhan S strain and decreases over time for the subsequent emerging variants of concern (VOC), with Omicron providing the weakest effect. We developed pseudo-typed viral particle (PVP) viral tools that allowed for the generation of cell lines constitutively expressing the four SARS-CoV-2 structural proteins and utilising the VSV-g envelope protein to deliver the integrated gene construct. Differential gene expression analysis (DGEA) was performed on cells expressing S, E, M, or N to determine cell activation status. Gene expression differences were found in a number of interferon-stimulated genes (ISGs), including IF16, IFIT1, IFIT2, and ISG15, as well as for a number of heat shock protein (HSP) genes, including HSPH1, HSPA6, and HSPBP1, with all four SARS-CoV-2 structural proteins. There were also differences observed in expression patterns of transcription factors, with both SP1 and MAVS upregulated in the presence of S, M, and E but not the N protein. Collectively, the results indicate that gene expression patterns associated with ER stress pathways can be activated by SARS-CoV-2 envelope glycoprotein expression. The results suggest the SARS-CoV-2 infection can modulate an array of cell pathways, resulting in disruption to NF-κB signalling, hence providing alterations to multiple physiological responses of SARS-CoV-2-infected cells.

Introduction: It is widely but erroneously believed that drugs get into cells by passing through the phospholipid bilayer portion of the plasma and other membranes. Much evidence shows, however, that this is not the case, and that drugs cross biomembranes by hitchhiking on transporters for other natural molecules to which these drugs are structurally similar. Untargeted metabolomics can provide a method for determining the differential uptake of such metabolites. Objectives: Blood serum contains many thousands of molecules and provides a convenient source of biologically relevant metabolites. Our objective was to measure them. Methods: We develop an untargeted LC-MS/MS method to detect a broad range of compounds present in human serum. We apply this to the analysis of the time course of the uptake and secretion of metabolites in serum by several human cell lines, by analysing changes in the serum that represents the extracellular phase (the ‘exometabolome’ or metabolic footprint). Results: Our method measures some 4,000-5,000 metabolic features in both ES ⁺ and ES ⁻ modes. We show that the metabolic footprints of different cell lines differ greatly from each other. Conclusion: Our new, 15-minute untargeted metabolome method allows for the robust and convenient measurement of differences in the uptake of serum compounds by cell lines following incubation in serum, and its relation to differences in transporter expression.