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Accelerate Your Research with Advanced Omics Solutions

Others, Presentations | 2018 | Agilent TechnologiesInstrumentation
GC/MSD, GC/MS/MS, GC/HRMS, Sample Preparation, GC/Q-TOF, LC/TOF, LC/HRMS, LC/MS, LC/MS/MS
Industries
Proteomics , Metabolomics
Manufacturer
Agilent Technologies

Summary

Importance of Multi-Omics Integration


Multi-omics approaches combine genomic, transcriptomic, proteomic, and metabolomic data to capture complex biological regulation and provide a comprehensive view of cellular function. This integration is essential for deciphering disease mechanisms, identifying biomarkers, and guiding targeted interventions.

Objectives and Overview


The presentation outlines Agilent’s suite of solutions designed to streamline research workflows. It covers advanced sample prep methods, high-performance mass spectrometry platforms, data acquisition techniques, and software for feature extraction, statistical analysis, and pathway mapping.

Methodology and Instrumentation


  • Sample preparation: Captiva EMR-Lipid cleanup for phospholipid removal and protein precipitation workflows.
  • Chromatography: Poroshell HILIC-Z columns for amino acid and metabolite separation, UHPLC, CE, and SFC techniques.
  • Mass spectrometry platforms: GC/MS (5977B), GC/QQQ (7000D), GC/Q-TOF (7200B), LC/Q-TOF (6500 series, Hi-DEF), LC/QQQ (6400/6460/6470), and Jet Stream ion source.
  • Software: MassHunter Core, Profinder, Mass Profiler Professional, Pathway Architect, Profiler, Agilent METLIN and Fiehn libraries, VistaFlux for isotope tracing, Spectrum Mill, Skyline, and IM Browser.

Main Results and Discussion


  • Captiva EMR-Lipid achieves over 99% removal of phospholipids across diverse biological fluids, enhancing LC/MS performance.
  • HILIC-Z workflows deliver robust quantification of amino acids and central carbon metabolites in cell culture media, revealing time-dependent consumption and secretion profiles.
  • Stable isotope tracing with VistaFlux allows qualitative flux analysis, tracking 13C incorporation into metabolic pathways and illustrating altered purine metabolism upon methotrexate treatment.
  • Seahorse XF Real-Time ATP Rate Assay differentiates glycolytic and mitochondrial ATP production rates, uncovering dynamic changes in cellular energy demand.
  • Proteomics workflows utilizing Jet Stream source and IM All Ions MS/MS improve sensitivity, enable drift-separated fragment ion analysis, and support both discovery and targeted studies.
  • Integrated software tools facilitate high-throughput feature finding, alignment, statistical analysis, and pathway-centric visualization of multi-omics datasets.

Benefits and Practical Applications


  • Streamlined workflows reduce sample handling time and minimize errors in complex analyses.
  • High resolution and sensitivity across platforms improve detection limits and quantitative accuracy.
  • Automated software pipelines enable efficient data processing, hypothesis testing, and visual interpretation.
  • Pathway mapping directly links multi-omics data to biological context, accelerating discovery of novel biomarkers and therapeutic targets.

Future Trends and Opportunities


  • Expansion of ion mobility and low-energy fragmentation methods to enhance structural characterization.
  • Growth of AI and machine learning for predictive models and automated annotation in omics data analysis.
  • Development of real-time, in situ assays for cellular metabolism and flux with higher throughput and multiplexing.
  • Integration of single-cell omics and spatially resolved techniques to study heterogeneity within tissues.

Conclusion


Agilent’s advanced omics solutions provide a cohesive, pathway-centric framework that accelerates research from sample preparation to data interpretation. By combining robust instrumentation and integrated software, researchers can achieve deeper mechanistic insights, improve analytical reproducibility, and drive innovation in biological and clinical studies.

Reference


  • Buckenmaier S, Miller CA, van de Goor T, Dittmann MM. J Chromatogr A. 2015;1377:64–74.

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