SARS-CoV-2 ncrRNA interactome

Published: 31 March 2022| Version 1 | DOI: 10.17632/4958h9zkty.1
Liuyiqi Jiang


A deep understanding of SARS-CoV-2-host interactions is crucial to developing effective therapeutics and addressing the threat of emerging coronavirus. The role of non-coding regions of viral RNA (ncrRNAs) has not been systematically scrutinized. We developed a method using MS2 affinity purification coupled with liquid chromatography-mass spectrometry (MAMS) to systematically map the interactome of SARS-CoV-2 ncrRNA in Calu-3, Huh7, and HEK293T cells. Integration of the results defined the core ncrRNA-host protein interactomes.


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Digested peptides were analyzed on an Q Exactive HF-X mass spectrometry system (Thermo Fisher Scientific) equipped with an Easy-nLC 1200 liquid chromatography system (Thermo Fisher Scientific). Samples were injected on a C18 reverse phase column (75 μm × 15 cm, 1.9 μm C18, 5 m tip). Mobile phase A consisted of 0.1% FA, and mobile phase B consisted of 0.1% FA/80% ACN. Peptides were analyzed with a 60 minutes linear gradient at flow rate 200 nL minutes−1 as the following: 0–5% B for 2 minutes, 5–35% B for 46 minutes, 35–100% B in 12 minutes. Data dependent analysis (DDA) was performed by acquiring a full scan over a m/z range of 350-1500 in the Orbitrap at R = 60,000 (m/z = 200), NCE = 27, with a normalized AGC target of 3 × 106, an isolation width of 0.8 m/z. The AGC targets and maximum ion injection time for the MS2 scans were 3 × 105 and 60 ms, respectively. Precursors of the + 1, + 8 or above, or unassigned charge states were rejected; exclusion of isotopes was disabled; dynamic exclusion was set to 45 s. Mass spectrometry data were searched by MaxQuant (Version All data were searched against the SwissProt Human protein sequences. Peptide and protein identification as well as label-free quantitation were performed; false-discovery rate (FDR) was set to 1%; fixed modification was carbamidomethyl; main search peptide tolerance was 10 ppm. MaxQuant outputs were used for downstream analysis. For each biological replicate, proteins that meet any of the following criteria are filtered out: 1. flagged as potential contaminants; 2. flagged as reverse sequences; 3. only identified by site; 4. quantified by a single razor or unique peptide; 5. only quantified by three or less than three unique peptides; and 6. only detected once in all samples. After filtering, we removed one anomalous technical replicate of NRC6 in Huh7 cells and one anomalous biological replicate of NRC4 in the HEK293T cells. Missing data imputation was performed for proteins with missing values in one technical replicate, while present in the other two replicates. Imputation was performed using mean value of the other two technical replicates. Finally, 541, 372, and 312 proteins were detected in Calu-3, Huh7, and HEK293T cells, respectively. For data normalization, NormalyzerDE (version 1.5.4) was applied to select the best normalization method. Based the results of pooled estimate of variance (PEV), coefficient of variation (CV), median absolute deviation (MAD), and correlation analyses, we chose the VSN as the normalization method. To remove the batch effects and correct data, we performed the ComBat method using the R package ‘sva’ (version 3.38.0). The outputs of Combat were used for further analysis.


Zhejiang University


Severe Acute Respiratory Syndrome Coronavirus 2