IMSC: Improvements in LFQ for reproducible quantification of proteomic experiments: how DDA outperform DIA

Significance of the Topic

The ability to quantify proteins accurately and reproducibly is central to modern proteomics. Label-free quantitation (LFQ) workflows inform biomarker discovery, quality control in bioproduction, and fundamental biology studies. By comparing two high-resolution acquisition strategies on Orbitrap platforms, this work highlights the optimal approach for deep and reliable proteome coverage.

Objectives and Study Overview

This study directly contrasts high-resolution accurate mass (HRAM) quadrupole-Orbitrap data-dependent acquisition (DDA) with data-independent acquisition (DIA) using the same chromatographic setups. Key goals include evaluating sensitivity, peptide and protein identification rates, quantitative reproducibility, and the impact of column length on performance.

Methodology and Instrumentation

Sample Preparation

• HeLa protein digest spiked with HRM peptide standards in 0.1% formic acid.
• Solvents: A (water, 0.1% formic acid), B (80% acetonitrile, 20% water, 0.1% formic acid).

Liquid Chromatography–Mass Spectrometry

• Thermo Scientific EASY-nLC 1200 system in direct-injection mode (2 µL, ~1 µg digest).
• Acclaim PepMap columns (50 cm or 75 cm × 75 µm ID, 2 µm particles) at 55 °C, gradient 5–44% B over 120 min at 300 nL/min.
• Thermo Scientific Q Exactive HF MS operated in DDA and DIA modes.

Data Analysis

• DDA raw files processed in Proteome Discoverer 2.2 using SEQUEST HT search against UniProt human database (42,085 entries), 1% FDR via Percolator.
• Quantitation via Minora feature detector, RT aligner and feature mapper nodes.
• DIA MS1 data processed in Spectronaut 9.0 against the DDA-derived spectral library.

Key Results and Discussion

Identification and Quantitation

• DDA on 75 cm column yielded ~40,230 peptides and 5,070 proteins versus ~32,013 peptides and 4,828 proteins on 50 cm.
• Quantifiable peptides (CV<20%) increased from ~16,968 (50 cm) to ~24,426 (75 cm).
• DDA outperformed DIA in proteome depth and reproducibility; peptide retention times and protein abundance correlations were high (r≈0.96).

Reproducibility and Coverage

• Library-free DDA workflow avoided DIA spectral library generation overhead.
• Column extension from 50 cm to 75 cm notably enhanced identification rates without compromising run stability.

Benefits and Practical Applications

• Improved sensitivity and deeper proteome coverage strengthen biomarker and target discovery.
• High inter-run reproducibility supports robust QC in regulated environments.
• Software-integrated LFQ streamlines data processing, normalization, and study management.

Future Trends and Applications

• Further hardware improvements (column chemistries, ion optics) for even greater depth.
• Hybrid DDA-DIA strategies may exploit strengths of both acquisitions.
• Advanced algorithms (machine-learning-based feature detection) to enhance quantitation sensitivity.
• Application to single-cell and spatial proteomics for high-resolution biological insights.

Conclusion

An untargeted DDA workflow on HRAM quadrupole-Orbitrap platforms, combined with advanced label-free quantitation software, surpasses DIA in identification depth, quantitative reproducibility, and operational efficiency, particularly when using extended chromatographic columns.