Scaling-up low input spatial proteomics using Evosep Eno on the timsUltra AIP

Significance of the Topic

Spatial proteomics of formalin-fixed paraffin-embedded (FFPE) tissue at ultra-low input levels enables high-resolution mapping of proteome heterogeneity across biological systems. Achieving both rapid throughput and deep coverage is essential for cohort-scale studies, biomarker discovery, and fundamental research into tissue microenvironments. The combination of high-speed chromatography and advanced trapped ion mobility spectrometry mass spectrometry (timsUltra AIP) addresses the dual challenge of sensitivity and throughput in spatial proteomics.

Study Objectives and Overview

This work evaluates the performance of a new Evosep Eno Whisper Zoom chromatography method coupled to the timsUltra AIP platform. Key goals include:

• Assessing protein and peptide identifications across gradient speeds from 500 to 30 samples per day (SPD).
• Comparing Evosep Eno to the standard Evosep One workflow.
• Demonstrating applicability to ultra-low input spatial regions (8,000 – 100,000 µm²) from mouse liver and human tonsil FFPE sections.
• Evaluating reproducibility and quantitative depth using DIA-PASEF and diagonal-PASEF acquisition modes analyzed with Spectronaut 19.

Experimental Methodology

Mouse liver and human tonsil FFPE sections (5 µm) were laser microdissected into 8,000–100,000 µm² regions. Samples underwent antigen retrieval at 65 °C, reduction/alkylation, and on-chip digestion using Cellenion proteoCHIP EVO-96 with LysC/trypsin on a cellenOne dispenser. Peptides were transferred to Evotips. Chromatography was performed on both Evosep One and the Evosep Eno Whisper Zoom method at 500, 300, 200, 100, 60, and 30 SPD. Mass spectrometry utilized a timsTOF Ultra 2 (timsUltra AIP) in DIA-PASEF and diagonal-PASEF modes with variable window schemes and accumulation times optimized per gradient speed. Data were processed in Spectronaut 19 using directDIA+ algorithms.

Used Instrumentation

• Laser microdissection system for FFPE tissue sampling
• Cellenion proteoCHIP EVO-96 and cellenOne dispenser
• Evosep One and Evosep Eno Whisper Zoom LC systems
• Bruker timsTOF Ultra 2 with timsUltra AIP
• Spectronaut 19 software for DIA analysis

Main Results and Discussion

Evosep Eno increased protein group identifications by ~30% and peptides by ~40% at 500 SPD versus standard methods. In HeLa dilution series (0.25–100 ng), >1,500 proteins were identified at 500 SPD, rising to ~4,200 at 30 SPD; the highest load at 30 SPD yielded ~8,400 proteins. Spatial regions from mouse liver (8,000 µm²) delivered ~2,800 proteins at 120 SPD and ~4,400 at 20 SPD; human tonsil regions showed similar performance. Data points per peak reached ~11, and Pearson correlations among methods exceeded 0.9, indicating high quantitative reproducibility. Principal component analysis distinguished epithelial, stromal, and immune niches; volcano plots highlighted region-specific protein markers.

Practical Implications and Applications

The combined Evosep Eno and timsUltra AIP workflow provides a robust, high-throughput solution for spatial tissue proteomics down to single-cell equivalent inputs. It supports large sample cohorts, minimizes sample loss in FFPE contexts, and delivers consistent quantitative data, facilitating biomarker discovery and tissue microenvironment studies.

Future Trends and Applications

Anticipated developments include integration with single-cell and multi-omics platforms, adaptive acquisition schemes using machine learning, further miniaturization of chromatography, expansion of timsUltra AIP ion mobility capabilities, and real-time data analysis to guide acquisition in complex tissue landscapes.

Conclusion

The novel Evosep Eno Whisper Zoom methodology on the timsUltra AIP significantly enhances throughput, sensitivity, and reproducibility for ultra-low input spatial proteomics. This scalable platform is well suited for high-content profiling of FFPE tissues, enabling new insights into tissue heterogeneity and disease mechanisms.

References

• Makhmut, A. et al. Cell Systems 14(11):1002-1014.e5 (2023).
• Skowronek, P.; Mann, M. Mol. Cell Proteomics 21(9):100279 (2022).
• Bruker Daltonics Application Note LCMS-193, LCMS-194, LCMS-206, LCMS-213, LCMS-222, LCMS-228, LCMS-233, LCMS-238 (2022-2025).