The Trans-omics Landscape of COVID-19

Abstract

The outbreak of coronavirus disease 2019 (COVID-19) has been causing a global health emergency. Although previous studies investigated COVID-19 at different omics levels, the molecular hallmarks of COVID-19, especially in those patients without comorbidities, have not been fully investigated. Here, we presented a trans-omics landscape for COVID-19 based on integrative analysis of genomic, transcriptomic, proteomic, metabolomic and lipidomic profiles from blood samples of 231 COVID-19 patients, ranging from asymptomatic to critically ill, importantly excluding those with any comorbidities. Notably, we found neutrophils heterogeneity existed between asymptomatic and critically ill patients. Expression discordance of inflammatory cytokines at mRNA and protein levels in asymptomatic patients could possibly be explained by post-transcriptional regulation by RNA binding proteins (RBPs) and microRNAs. Neutrophils over-activation, induced arginine depletion, and tryptophan metabolites accumulation contributed to T/NK cell dysfunction in critical patients. Anti-virus interferons were gradually suppressed along with disease severity. Overall, our study systematically revealed multi-omics characteristics of COVID-19, and the data we generated could hopefully help illuminate COVID-19 pathogenesis and provide valuable clues about potential therapeutic strategies for COVID-19.

Longitudinal multi-omics transition associated with fatality in critically ill COVID-19 patients

“…Blood sample collection, blood cell separation, blood cell preservation, and serum preservation followed previous study [21]. After standard diagnostic tests, all anticoagulated venous blood samples treated with ethylenediaminetetraacetic acid disodium salt (EDTA-2Na) were separated by centrifugation at 3000 rpm, then rested at room temperature for 7 min.…”

“…The mRNA library construction was performed as previously reported [21]. In total, 113 transcriptome profiles were generated as follows: (1) rRNA was removed using RNase H; (2) globin RNA was removed using a QAIseq FastSelect RNA Removal Kit; (3) cDNA fragments purified by magnetic beads were successively mixed with End Repair Mix, and A-Tailing Mix by pipetting, followed by incubation; (4) PCR amplification; (5) library quality control and pooling cyclization were conducted.…”

“…Sera samples were processed as described previously [21] using data-independent acquisition [22] strategy based on UltiMate 3000 UHPLC liquid chromatography (Thermo Scientific, San Jose, USA) and Q Exactive HF mass spectrometer (Thermo Scientific, San Jose, USA). Spectronaut software was utilized to analyze the raw data obtained from 85 samples with default settings.…”

“…In total, 100 μL of serum from each sample was analyzed using a spectrometer, LC following previous procedures [21]. Raw metabolite data obtained from 85 samples were analyzed using Compound Discoverer v3.1 (Thermo Fisher Scientific, USA).…”