Leveraging the Orbitrap astral mass spectrometer to enable the analysis of low tissue content sample sources

Analysis of cancer cohorts can face sample limitations due to insufficient sample tissue. This may be due to tumour specimens collected for pathology stains to assist in disease characterisation during cancer diagnosis. Further, the analysis of tissue samples from Laser Capture Microdissection (LCM) and tissue microarrays (TMA) that can provide a valuable source of proteomics information are limited due to insufficient tissue for proteomics. The sensitivity and speed of current generation mass analysers for proteomics have been a limiting factors in analysing smaller tissue samples. Our aim was to utilise the enhanced sensitivity of the Orbitrap Astral mass spectrometer to determine its ability to analyse smaller tissue samples, with minimal loss in peptide and protein identification while maintaining quantitative accuracy.

To test the Orbitrap Astral sensitivity and scalability, HEK-290 cell line digests were initially used at varying sample loads (2 ng-500 ng). While low sample loads can benefit from nanoflow, the extended un-utilised idle time at the start of a run and the challenges associated with nanoflow robustness suggested use of microflow over nanoflow. To balance the robustness of microflow with the sensitivity gains of nanoflow, a low microflow rate of 1.5 μL/min and a 150 μm ID column were used.

With a 500 ng peptide load of HEK-293 digest and a 13-minute gradient, DIA analysis identified nearly 9,000 protein groups and over 150,000 peptides. This decreased to 8,500 proteins and 120,000 peptides with a 200 ng load. At minimal loads of 10 ng and 2 ng, more than 4,500 and 2,500 proteins, respectively, were identified.

To enhance peptide and protein identification for low on-column load samples, such as LCM and TMA samples, we tested the impact of different accumulation times, DIA window sizes, and precursor mass ranges using HEK-293 digest at low on-column loads (2ng-10ng). After optimization, there was a 30% increase in the number of identified proteins. This emphasizes the significance of precisely adjusting these parameters, especially when dealing with low quantity samples.

The quantitative accuracy of the Orbitrap Astral was then assessed at low loads using a three-species mix of Human, E. coli and Yeast at varying ratios. Loads ranging from 2 -50 ng were compared with a 200 ng load. The instrument consistently maintained good quantitative accuracy across the low loads, while increasing on-column loads demonstrating improved quantitative performance especially for low abundant peptides and proteins.

The data demonstrates the effectiveness of the Orbitrap Astral to achieve high sensitivity and accuracy with far smaller sample requirements, expanding sample access to smaller specimens such as those acquired from LCM or TMAs.