ABSTRACT
We present compelling evidence for the existence of an evolutionary adaptive response to viral agents such as SARS-CoV-2, that results in the human in vivo biosynthesis of a family of compounds with potential antiviral activity. Using nuclear magnetic resonance (NMR) spectroscopy, we detected a characteristic spin-system motif indicative of the presence of an extended panel of urinary and serum metabolites during the acute viral phase. The structure of eight of nucleoside analogues was elucidated (six of which have not previously been reported in human urine), and subsequently confirmed by total-synthesis and matrix spiking. The molecular structures of the nucleoside analogues and their correlation with an array of serum cytokines, including IFN-2, IFN-{gamma} and IL-10, suggest an association with the viperin enzyme contributing to an endogenous innate immune defense mechanism against viral infection.
Subject(s)
Virus Diseases , COVID-19ABSTRACT
The biology driving individual patient responses to SARS-CoV-2 infection remains ill understood. Here, we developed a patient-centric framework leveraging detailed longitudinal phenotyping data, covering a year post disease onset, from 215 SARS-CoV-2 infected subjects with differing disease severities. Our analyses revealed distinct "systemic recovery" profiles with specific progression and resolution of the inflammatory, immune, metabolic and clinical responses, over weeks to several months after infection. In particular, we found a strong intra-patient temporal covariation of innate immune cell numbers, kynurenine- and host lipid-metabolites, which suggested candidate immunometabolic pathways putatively influencing restoration of homeostasis, the risk of death and of long COVID. Based on these data, we identified a composite signature predictive of systemic recovery on the patient level, using a joint model on cellular and molecular parameters measured soon after disease onset. New predictions can be generated using the online tool http://shiny.mrc-bsu.cam.ac.uk/apps/covid-systemic-recovery-prediction-app, designed to test our findings prospectively.