Increased sensitivity for low-input label-free proteomics using the Orbitrap Astral MS and μPAC Neo Plus Columns

Significance of the topic

Low-input, label-free proteomics addresses critical analytical needs where sample material is severely limited (single cells, microdissected tissue, rare clinical material). Improving sensitivity, quantitative precision, and proteome coverage at picogram-to-nanogram inputs expands biological insight into heterogeneous systems while avoiding labeling complexity. Combining high-sensitivity mass analyzers with low-dispersion nanoflow chromatography and ion filtering technologies enables reliable protein identification and LFQ in these challenging regimes.

Goals and study overview

This technical note evaluates peptide/protein identification depth and quantitative precision at low sample loads using data-independent acquisition (DIA) on the Thermo Scientific Orbitrap Astral Mass Spectrometer paired with the Vanquish Neo UHPLC and μPAC Neo Plus 50 cm micro-pillar array column. Key aims were:

• Assess identification and quantitation across a HeLa digest dilution series (50 pg–20 ng).
• Compare μPAC Neo Plus 50 cm column performance to a conventional 75 μm I.D. × 25 cm pulled-tip packed column.
• Optimize Astral MS DIA parameters based on load and evaluate FAIMS compensation voltage strategies.
• Test direct injection versus trap-and-elute workflows and multiple sample-throughput regimes (20–100 samples per day, SPD).

Methodology and instrumentation

Experimental design and sample handling:

• Sample: Pierce HeLa Protein Digest Standard reconstituted and diluted to final loads between 50 pg and 20 ng; triplicate injections for each load.
• Label-free quantitation using DIA acquisition and Spectronaut 19.9 for data processing with 1% FDR for peptides/protein groups.

LC-MS strategies and optimization summary:

• DIA with load-dependent tuning: wider isolation windows and longer Astral injection times were used at lower loads to boost sensitivity; higher loads used narrower windows and shorter injection times to preserve selectivity and dynamic range.
• Throughput tested from 20 to 100 SPD; FAIMS Pro Duo evaluated with single and dual compensation voltages (CVs) to trade gradient length and throughput for depth.
• Direct injection and trap-and-elute (backward flush) workflows compared to enable fast loading/desalting of larger volumes while monitoring peak widths and identifications.

Instrumentation used

• Thermo Scientific Orbitrap Astral Mass Spectrometer (Astral analyzer coupled with Orbitrap Analyzer and high-resolution quadrupole).
• FAIMS Pro Duo interface for gas-phase ion filtering and compensation-voltage fractionation.
• Thermo Scientific Vanquish Neo UHPLC System with μPAC Neo Plus 50 cm HPLC Column and optional μPAC trapping column.
• EASY-Spray source and EASY-Spray emitter (10 μm I.D.), Sonation column oven for μPAC columns.
• Data analysis: Spectronaut 19.9 (primary), Thermo Proteome Discoverer and DIA-NN/Aptila tools mentioned for broader workflow compatibility.

Main results and discussion

Identification depth and precision:

• μPAC Neo Plus 50 cm column outperformed the 75 μm × 25 cm pulled-tip column notably at low inputs (<5 ng), with relative peptide identification gains ranging from ~6% to 33% as load decreased; gains in peptides with CV <20% ranged from 3% to 35% across the dilution series.
• Best overall identification counts for a 250 pg HeLa digest were obtained at 30–50 SPD, achieving over 49,000 peptides and more than 6,300 protein groups in the reported workflow.
• Protein-level reproducibility across throughput regimes was stable: median protein-group CVs ranged ~13.5%–15% across 20–100 SPD methods, with peptide and protein identifications remaining within ±10% and ±5% respectively when experiments were repeated 50 hours later.

MS parameter optimization and FAIMS effects:

• Load-dependent DIA optimization (isolation window and Astral injection time) preserves linearity and avoids wasting dynamic range; low-input runs used wider DIA windows and longer injection times to enhance detectability of low-abundance precursors.
• FAIMS reduced background and gas-phase fractionation improved identifications; using two FAIMS CVs with longer gradients increased peptide identifications by ~37% on average and produced a ~5% increase in protein groups compared with single-CV, higher-throughput conditions.

Trap-and-elute workflow performance:

• Trap-and-elute allowed rapid loading/desalting of larger volumes (<3 min) and retained comparable identification performance to direct injection despite modest peak broadening.
• At constant 250 pg load, moderate injection volumes (0.05–0.25 μL) performed comparably; increasing injection volume to 7.5 μL (lower concentration) reduced peptide IDs by ~13%, indicating adsorption/loss risks at dilute sample conditions.
• Switching weak-wash solvent to 0.1% TFA narrowed peaks (~8% base width reduction) but caused a small drop (2%–4%) in identifications, likely due to ion suppression.

Benefits and practical applications of the method

• The Astral MS combined with μPAC Nanoarchitecture improves sensitivity and peak quality for low-input LFQ proteomics, enabling deeper coverage from sub-nanogram samples.
• Load-optimized DIA parameters and FAIMS integration provide a practical route to balance throughput and depth—suitable for labs needing scalable pipelines from single-cell to low-microgram loads.
• Trap-and-elute workflows support flexible sample handling (larger volumes, desalting) for challenging matrices while keeping run times short, valuable for high-throughput studies or cohorts with limited material.

Future trends and potential applications

• Further automation and integration of load-adaptive acquisition schemes (real-time adjustment of isolation windows and injection times) will streamline sensitivity gains without manual method switching.
• Combining microfabricated columns (μPAC) with enhanced ion mobility or FAIMS multi-CV routines and advanced library-free DIA software is expected to further expand proteome depth for single-cell and spatial proteomics.
• Engineering of sample containers and low-adsorption consumables to minimize peptide loss at low concentrations will raise effective throughput and reliability for very dilute injections.

Conclusion

The study demonstrates that pairing the Orbitrap Astral MS with μPAC Neo Plus 50 cm columns and FAIMS yields robust, sensitive label-free DIA proteomics at very low sample inputs. Load-dependent DIA optimization and appropriate FAIMS strategies substantially increase peptide and protein identifications and preserve quantitative precision. Trap-and-elute workflows provide practical flexibility for handling larger injection volumes with minimal penalty. Overall, the described configuration supports reproducible high-sensitivity LFQ for applications ranging from single-cell workflows to low-input clinical and research samples.

References

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2. Thermo Fisher Scientific. μPAC Neo Plus HPLC columns: Use and care instructions (Instruction Sheet DOC018). 2025.
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