Lecture

Extending the application range of ICP-MS in the life sciences

  • at -
  • ICM Saal 5
  • Type: Lecture

Lecture description

ICP-mass spectrometry (ICP-MS) has become a routine tool in clinical laboratories for quantifying elements in various biofluids, but its potential in the life sciences extends far beyond this.
When combined with laser ablation (LA) for sample introduction, ICP-MS enables quantitative mapping of elemental distributions across tissue sections. Recent advances in ablation cell and transfer line design have reduced the single-pulse response (transient signal as observed after a single firing of the laser) duration to below 1 ms, allowing pixel acquisition rates up to 1,000 Hz. Using ICP-MS with a time-of-flight (ToF) analyzer further enhances this approach, as each pixel provides multi-element data across nearly the entire periodic table.
The high sensitivity of ICP-MS also supports quantitative analysis of exogenous and endogenous elements at the single-cell level. This can be achieved using either LA sampling for both adherent and non-adherent cells or pneumatic nebulization of cell suspensions. Although ToF-ICP-MS offers lower sensitivity than quadrupole-based systems, it provides superior reliability by enabling the use of a cell marker, normalization to cell size, and multi-element correlation analysis.
Finally, next to their concentration, also the isotopic composition of essential mineral elements provides useful information. Multi-collector ICP-MS enables natural variation in the isotopic composition of such elements to be revealed and quantified. In many contexts, isotope ratios have been demonstrated to be more sensitive in picking up changes in biochemical processes accompanying the development or progress of a disorder and/or provide complementary information not embedded in the concentration data.
At Ghent University’s Atomic and Mass Spectrometry (A&MS) research group, we develop, optimize, and validate such analytical methods and apply them to real-world biological questions. Selected examples will illustrate how these approaches deliver unique and complementary information in life sciences research.
#analytica
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