AcquireX Intelligent Data Acquisition Technology - Collect more meaningful data, not just more data

Significance of the Topic

Comprehensive profiling of small molecules is pivotal for applications ranging from metabolomics to quality control. Traditional data-dependent acquisition (DDA) methods often undersample low-abundance compounds and require laborious manual method development. Intelligent automation that selectively targets novel features can dramatically improve data quality, accelerate workflows, and enhance confidence in compound identification.

Objectives and Study Overview

This study introduces Thermo Scientific™ AcquireX™ intelligent data acquisition technology, which automates the creation of inclusion and exclusion lists to guide high-resolution accurate-mass (HRAM) MS and multi-stage MSn experiments. The primary goals are to exhaustively interrogate precursors, minimize redundant sampling, and maximize the depth and confidence of small-molecule characterization across complex matrices.

Methodology and Instrumentation

AcquireX employs a multi‐step workflow:

• Background mapping: HRAM full‐scan LC-MS of blank or matrix samples defines features to exclude.
• Target mapping: Representative study samples generate a list of relevant precursor ions for inclusion.
• Automated iterative acquisition: Inclusion/exclusion lists are updated after each replicate, directing DDA to novel features until exhaustion criteria are met.

Key instrumentation and software components include:

• Thermo Scientific™ Orbitrap™ mass spectrometer for HRAM MS, MS/MS, and MSn acquisition.
• Xcalibur™ control software (v4.2 or higher) and Tune (v3.1 or higher) for experiment setup.
• Compound Discoverer™ (v3.0+) with mzLogic™ algorithm and Mass Frontier™ (v8.0+) for database and spectral library searching.
• Thermo Scientific™ mzCloud™ high-resolution fragmentation library for spectral matching.

Key Results and Discussion

Application of AcquireX showed significant improvements in feature coverage and data quality:

• Reduction of redundant MS/MS events by dynamically excluding background and previously sampled precursors.
• Enhanced detection of low-intensity and adduct species by grouping related features and regenerating inclusion lists.
• Increased depth of MSn fragmentation, enabling richer product‐ion spectra and more reliable structural elucidation.
• Fewer replicate injections required to saturate compound sampling, saving instrument time and sample material.

Chromatographic reproducibility and high mass resolving power (>60,000) were critical to accurately map and distinguish isobaric features across runs.

Benefits and Practical Applications

AcquireX offers multiple advantages for small‐molecule research and routine analysis:

• Automated workflow reduces manual method development and operator bias.
• Comprehensive precursor selection ensures exhaustive compound profiling in metabolomics, environmental screening, and extractables/leachables analysis.
• High‐confidence compound identification through integrated database and spectral library searches, supported by deep MSn datasets.
• Improved laboratory throughput and reproducibility, facilitating QA/QC and regulatory compliance.

Future Trends and Potential Applications

Building on intelligent acquisition, future developments may include:

• Real‐time machine learning algorithms to predict fragmentation efficiency and guide adaptive MSn workflows.
• Integration with multi‐omics platforms for correlated metabolite, lipid, and proteome data acquisition.
• Expansion of dynamic exclusion/inclusion strategies to ion mobility and fragmentation pattern recognition.
• Cloud‐based data processing and spectral library updates to leverage community‐driven compound annotations.

Conclusion

Thermo Scientific™ AcquireX™ streamlines small‐molecule LC‐MS workflows by automating exhaustive precursor mapping and intelligent MSn acquisition. This approach enhances the detection of low‐abundance analytes, reduces redundant sampling, and delivers high‐confidence structural information, ultimately accelerating research and quality control applications.

References

No formal literature citations were provided in the original document.