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Session: Session 5

Development of Thermal Proteome Profiling (TPP) for identification and quantification of Sars-CoV-2 proteic interactants using Tandem Mass Tag (TMT)

Valériane GAXOTTE1, Aurélie HIRSCHLER1, François DELALANDE1, Adrien BROWN1, Malvina SCHATZ2, Yonis BARE2, Raphael GAUDIN2, Christine CARAPITO1

1LSMBO IPHC UMR 7178 Université de Strasbourg CNRS ProFI FR2048, Strasbourg, France
2MDV IRIM UMR 9004 Université de Montpellier CNRS , Montpellier, France

Objectives: TPP was developed to identify drug-binding targets by analyzing the impact on interacting proteins’ thermal stability of the binding of a drug molecule without requiring compound modification or candidate protein purification. To detect and identify ligand-induced shifts of thermal stability curves and thus drug target in the case of SARS-COV-2, an optimized and multiplexed quantification workflow using isobaric labelling with TMT (Tandem Mass Tag) was applied over a temperature gradient.

 

Methods: To obtain a final thermal curve, a gradient composed of 16 temperatures was applied on 5 conditions: infected cells, positive control (non-infected cells with addition of drug), non-infected and non-treated cells, infected cells with the functional drug and finally, negative control (infected cells with a non-functional drug).

After a centrifugation step, proteins contained in the supernatant of each condition were digested by SP3 (Single Plot Solid Phase enhanced Sample Preparation), then labelled by TMT-16plex. One pool was obtained per condition and further C-18 desalted. The labelled peptide mixture was analyzed on a nanoAcquity system coupled to an Orbitrap Eclipse Tribrid mass spectrometer (Thermo Scientific). Data processing was done using Proteome Discoverer and Statistical Analysis with a TPP-package in R.

 

Results: More than 1500 proteins were quantified in the five conditions and thermal stability curves could be drawn for all of them. As promising results, a list of candidate proteins with significant thermal shifts were selected and are in the process of being validated.

 

Conclusion: While those initial results are encouraging, further optimizations are still required especially at the sample design and data treatment steps.