Argon gas cluster ion beam used to identify intact proteins through enzymatic digestion

Using argon gas ion beams (Ar-GCIB) for time-of-flight secondary ion mass spectrometry (ToF-SIMS) studies is a promising way to detect intact proteins and determine their amino acid sequences while minimizing sample damage. Son et al. used the technique to identify proteins through enzymatic digestion in a bottom-up approach and significantly improved the signal-to-noise ratio of intact proteins.

The researchers showed that the use of an Ar-GCIB in ToF-SIMS analysis for detection of intact proteins extended the dynamic range greater than an order of magnitude compared to the cluster bismuth polyatomic ion beam that has been used with regularity in recent years.

They also showed that Ar-GCIB ToF-SIMS detection of enzymatically digested proteins dried on silicon (Si) substrates was identical to in-solution detection.

“By introducing Ar-GCIB to surface protein analysis, the on-surface method opens up imaging analytical possibilities that are more suitable for analysis of animal tissue or a lab-on-chip approach than a typical in-solution method,” said author Jin Gyeong Son.

The researchers used trypsin in an ammonia bicarbonate buffer solution to digest aqueous myoglobin, cytochrome C and bovine serum albumin. For on-surface enzymatic digestion, protein solutions were loaded and ambiently dried on Si wafers and then sprayed with the trypsin solution, without the need to remove buffers or salts.

The Ar-GCIB was applied to the protein samples. The acceleration voltage of 20 kilovolts was key to improving the sign-to-noise ratio. The researchers confirmed the identity of the proteins by comparing their analyses with protein data from peptide sequence databases.

The goal of subsequent on-surface studies is to identify specific proteins in protein mixtures and analyze proteins present in biological tissue or chip sample surfaces.

Source: “Ar-gas cluster ion beam in ToF-SIMS for peptide and protein analysis,” by Jin Gyeong Son, Sohee Yoon, Hyun Kyong Shon, Jeong Hee Moon, Sunho Joh, and Tae Geol Lee, Biointerphases (2019). The article can be accessed at https://doi.org/10.1116/6.0000105 .