BayBioMS - Merits of proteomics for SARS-CoV2 research and testing

Data, reagents, assays and merits of proteomics for SARS-CoV-2 research and testing
Data License: CC BY 4.0 | ProteomeXchange: PXD019680
  • Organism: SARS-CoV-2, Homo sapiens
  • Instrument: Orbitrap Fusion Lumos
  • SpikeIn: Yes
  • Keywords: SARS-CoV-2, proteomics, mass spectrometry, stable isotope labeling, parallel reaction monitoring, Vero E6, ACE2, infectome, nasopharyngeal swabs
  • Lab head: Christina Ludwig Submitter: Christina Ludwig
Abstract
As the SARS-CoV-2 pandemic continues to spread, thousands of scientists around the globe have changed research direction to better understand how the virus works and to find out how it may be tackled. The number of manuscripts on pre-print servers is soaring and peer-reviewed publications using mass spectrometry-based proteomics are beginning to emerge. To facilitate proteomic research on SARS-CoV-2, this report presents deep-scale proteomes (10,000 proteins; >130,000 peptides) of common cell line models, notably Calu-3, CaCo-2, ACE-A549 and Vero E6 that characterizes their protein expression profile including viral entry factors such as ACE2 or TMPRSS2. Using the 9 kDa protein SRP9 and the oncogene breast BRCA1 as examples, we show how the proteome expression data can be used to refine the annotation of protein coding regions of the African green monkey genome. Monitoring changes of the proteome upon viral infection revealed widespread expression changes including transcriptional regulators, protease inhibitors and proteins involved in innate immunity. The extensive protein and peptide coverage obtained, can also be used to build spectral libraries for setting up data independent acquisition (DIA) or parallel reaction monitoring (PRM) experiments for host or viral proteins. Based on a library of 98 stable isotope labeled synthetic peptides representing 11 viral proteins, we developed PRM assays for nano-flow as well as micro-flow LC-MS/MS. We assessed the merits of these PRM assays by the analysis of supernatants of virus infected Vero E6 cells and challenged the assays by analyzing two diagnostic cohorts of 24 (+30) SARS-CoV-2 positive and 28 (+9) negative cases. In light of the results obtained, we critically discuss the merits of mass spectrometry-based proteomics for SARS-CoV-2 research and testing.
Experiment Description
Experimental design PRM In this work, using heavy synthetic peptide references, we generated a SARS-CoV-2 spectral library entailing fragment ion spectra and retention time information for 98 SARS-CoV-2 peptides. This was further refined to a parallel reaction monitoring (PRM) assay panel containing 23 peptides and applied to the detection of SARS-CoV-2 in two clinical cohorts. In total, 91 respiratory specimens, of which 37 were tested negative and 54 were tested positive for SARS-CoV-2 by rtPCR analyses, were analysed by nano- and micro-flow PRM using two different input quantities for the patient samples.
Sample Description
Sample preparation Synthetic, isotopically labeled SARS-CoV-2 peptides – In total, 113 isotopically labeled SpikeTidesTM peptides covering 11 SARS-CoV-2 proteins were kindly provided by JPT Peptide Technologies. In these peptides either the C-terminal lysine (Lys8) or arginine residue (Arg10) was 13C- and 15N-labeled. For peptides located at the C-terminus of a protein that do not entail a C-terminal lysine or arginine residue, Leucines were labeled with 13C and 15N (Leu7). For retention time calibration, PROCAL retention time peptides from JPT Peptide Technologies and indexed retention time (iRT) peptides from Biognosys were used. All quantities per spike-in peptide specified in the following represent only a rough estimate, as the isotopically labelled peptides were not purified and concentrations were not determined accurately. Collection of respiratory specimens – In this study, only specimens that were collected as part of the standard diagnostic testing performed within routine patient care, and that would normally be discarded, were used. Approval to do so was granted by the ethics committee of the University Hospital “rechts der Isar” of the Technical University of Munich. Patient identification was not recorded, and only SARS-CoV-2 proteins were investigated. For nasopharyngeal swabs a polyurethan swab (Sigma-swab, Medical wire) was inserted through the nasal canal to the nasopharynx, and specimen was dissolved in 1 ml fluid amies media (Sigma-Transwab®). Bronchoalveolar lavage (BAL) of the lower respiratory tract was performed using a fiber-optic bronchoscope and flushing with 0.9 % saline. Samples were stored at -80 °C until further analysis. Inactivation was performed by heating at 95 °C for 10 min. Cell culture - Vero E6 cells were cultured in DMEM complemented with 10 % FBS, 100 µg/ml Streptomycin and 100 IU/ml Penicillin. For infection Vero E6 cells were infected with SARS-CoV-2-MUN-IMB-1 strain using a multiplicities of infection (MOI) of 0.01. Supernatant of infected Vero E6 cells was collected 48 h post infection and spun twice at 6,000 g for 10 min. The virus-containing supernatant was heated at 95 °C for 5 to 10 min before storage at -80 °C. Sample preparation of a supernatant dilution series – A dilution series experiment using the virus supernatant sample was performed with 8 dilution steps: 15, 5, 1.5, 0.5, 0.15, 0.05, 0.015 and 0.005 μg of total protein amount. Dilutions were used as input for the in-gel digestion workflow. In parallel, a gel-band loaded with sample buffer only was processed representing a “blank” sample. The identical amount (~15 fmol) of isotopically labeled SARS-CoV-2 peptide mix was added to all 9 samples. Subsequently one-third of the sample was measured by nano-flow and two-third by micro-flow PRM, targeting 23 and 21 SARS-CoV-2 peptides, respectively. Sample preparation of respiratory specimens – For nano-flow PRM analysis of patient cohort 1, 15 µl of residual material from diagnostic testing of 52 patients was mixed 3:1 with 4x Novex NuPage LDS sample buffer containing 40 mM DTT and used as input for in-gel digestion. Isotopically labeled SARS-CoV-2 peptide mix (15 fmol) was spiked into all 52 swab samples directly before measurement. Additionally, PROCAL retention time peptides (JPT Peptide Technologies) and indexed retention time peptides (iRT, Biognosys) were added. Subsequently, one-third of the sample amount was injected into the mass spectrometer and measured by nano-flow PRM. For the micro-flow PRM measurements of cohort 1, in total 50 µl of each sample were mixed with 4x LDS sample buffer containing 40 mM DTT, added to two gel pockets, and combined after digestion. For cohort 2, up to 300 µl of 39 nasopharyngeal swab samples were dried down and resuspended in 25 µl of 2x Novex NuPage LDS sample buffer containing 10 mM DTT before subjection to in-gel digestion. Before micro-flow PRM measurement, heavy SARS-CoV-2 peptides (ca. 50 fmol/injection), PROCAL, and iRT peptides were spiked into all samples, followed by micro-flow PRM measurements. For the nano-flow setup all peptides corresponding to 5 µl of the original sample were used for PRM measurements, whereas for micro-flow analyses a quantity corresponding to 46.4 µl of the original sample was injected into the MS (equivalent to input amounts for standard rtPCR analyses). As negative/blank controls empty gel lanes were processed and analysed in parallel with the patient samples. PRM LC-MS/MS measurements Targeted PRM measurements were performed on the isotopically labeled synthetic peptide mixture, on a supernatant sample and dilutions of SARS-CoV-2 infected Vero E6 cells, and on two clinical cohorts of respiratory specimens from patients using a nano-flow and a micro-flow system. Nano flow: Nano-flow PRM measurements were performed using a 50 min linear gradient operating the Fusion Lumos in PRM mode. Targeted MS2 spectrum acquisition was performed at 60 k resolution within 100-2,000 m/z, after HCD with 30 % NCE, and using an AGC target value of 4e5 charges, a maxIT of 118 ms and an isolation window of 1.3 m/z. The number of targeted precursors was adjusted to a cycle time of at maximum 2 seconds. In initial evaluation runs using the isotopically labeled synthetic peptide mixture and the supernatant sample, 113 theoretical tryptic SARS-CoV-2 peptides were targeted in different charge states and in light and/or heavy form requiring partition of the precursor list over 6 to 8 injections per sample. For the PRM analysis of the dilution series samples and nasopharyngeal swab samples only 23 optimal SARS-CoV-2 peptide precursors, plus 11 iRT peptide precursors, were targeted within a single PRM measurement and with a 6 minutes schedule retention time window. Micro-flow: Micro-flow PRM measurements were performed using a 15 min linear gradient operating the Fusion Lumos in PRM mode. Targeted MS2 spectrum acquisition was performed at 60 k resolution within 100-2,000 m/z, after HCD with 32 % NCE, and using an AGC target value of 1e5 charges, a maxIT of 118 ms and an isolation window of 1.3 m/z. The number of targeted precursors was adjusted to a cycle time of at maximum 0.9 sec to obtain at least 6-7 data points per peak. In total, 21 SARS-CoV-2 peptides were targeted in 1 min wide transition windows. No peptides for retention time calibration were scheduled for fragmentation, but PROCAL peptides were spiked into samples to utilize MS1 chromatogram information. PRM data analysis Nano-flow and micro-flow PRM data were analyzed using the Skyline-daily (64-bit) software (version 20.1.1.83). For all target peptides the most intense precursor charge state and the 6 most-intense fragment ions were selected automatically by Skyline using the experimental spectral libraries generated from the synthetic peptide mixture measurements in nano- and micro-flow, respectively. The raw PRM data were imported into Skyline and peak integration and transition interferences were reviewed manually. If necessary, integration boundaries were manually adjusted and strongly interfered transitions were removed from the complete dataset, but keeping at least 5 transitions per peptide. Dilution series experiment: The linearity of the PRM-MS2 signal response was investigated for each targeted SARS-CoV-2 peptide within the dilution series experiment. A global SARS-CoV-2 response was determined by summing up PRM-MS2 intensities of all detectable light peptides at a given dilution step. The lowest dilution step of still confident detectability was determined by manual inspection. Three peptides that showed a confounding background signal in the blank and/or low concentration samples in the nano-flow dilution series (LNTDHSSSSDNIALLVQ, GFYAEGSR and FLPFQQFGR) were excluded from the analysis of the nano-flow clinical sample cohort 1. Clinical swab sample cohorts: To discriminate between positive and negative peptide detection in the clinical swab sample cohorts, three parameters were exported from Skyline: i) mass accuracy (“Average Mass Error PPM”), ii) correlation of fragment ion intensities between the light SARS-CoV-2 peptide measured by PRM and the experimental library spectrum (“Library Dot Product”), iii) correlation of fragment ion intensities between the light (endogenous) and heavy (spike-in) peptide measured by PRM (“DotProductLightToHeavy”). Only patients for which at least one light SARS-CoV-2 peptide fulfilled the following criteria were classified as “positive”: Average Mass Error PPM between 4 and -4 ppm, Library Dot Product > 0.85 and DotProductLightToHeavy > 0.90. The total SARS-CoV-2 intensity per patient was computed by summing up all light peptide intensities detected positive in a given patient. MS-system carry was monitored and minimized throughout all swab sample measurements by performing blank injections between each sample.
Created on 6/9/20, 1:28 PM

The data dependent acquisition proteomics raw data, complete MaxQuant search results and the searched protein sequence databases, that were used to build the spectral libries used in different Skyline documents, have been deposited with the ProteomeXchange Consortium (http://www.proteomexchange.org/) via the PRIDE partner repository and can be accessed using the data set identifier PXD019645.