Imaging mass spectrometry

Abstract. We have developed a laser ablation sampling technique for matrix-assisted laser desorption ionization (MALDI) mass spectrometry and tandem mass spectrometry (MS/MS) analyses of in-situ digested tissue proteins. Infrared laser ablation was used to remove biomolecules from tissue sections for collection by vacuum capture and analysis by MALDI. Ablation and transfer of compounds from tissue removes biomolecules from the tissue and allows further analysis of the collected material to facilitate their identification. Laser ablated material was captured in a vacuum aspirated pipette-tip packed with C18 stationary phase and the captured material was dissolved, eluted, and analyzed by MALDI. Rat brain and lung tissue sections 10 μm thick were processed by in-situ trypsin digestion after lipid and salt removal. The tryptic peptides were ablated with a focused mid-infrared laser, vacuum captured, and eluted with an acetonitrile/ water mixture. Eluted components were deposited on a MALDI target and mixed with matrix for mass spectrometry analysis. Initial experiments were conducted with peptide and protein standards for evaluation of transfer efficiency: a transfer efficiency of 16% was obtained using seven different standards. Laser ablation vacuum capture was applied to freshly digested tissue sections and compared with sections processed with conventional MALDI imaging. A greater signal intensity and lower background was observed in comparison with the conventional MALDI analysis. Tandem time-of-flight MALDI mass spectrometry was used for compound identification in the tissue.

Section: Introductionmentioning

confidence: 99%

Laser Ablation with Vacuum Capture for MALDI Mass Spectrometry of Tissue

Donnarumma

Cao

Murray

2015

“…The detector enables proteins up to 70 kDa to be imaged, and proteins up to 110 kDa to be detected, directly from tissue, and indicates new directions by which the mass range amenable to MALDI imaging MS and MALDI profiling MS may be extended. (J Am Soc Mass Spectrom 2010, 21, 1922-1929) © 2010 American Society for Mass Spectrometry S ince its inception ϳ10 y ago, MALDI imaging mass spectrometry (imaging MS) has developed into a powerful and versatile tool for biomedical research [1,2]. It is now routinely used for analyzing peptides and small proteins up to 25 kDa [3-6], administered drugs and their metabolites [7], and recently major improvements have been reported for lipids [8].…”

mentioning

confidence: 99%

“…S ince its inception ϳ10 y ago, MALDI imaging mass spectrometry (imaging MS) has developed into a powerful and versatile tool for biomedical research [1,2]. It is now routinely used for analyzing peptides and small proteins up to 25 kDa [3][4][5][6], administered drugs and their metabolites [7], and recently major improvements have been reported for lipids [8].…”

mentioning

confidence: 99%

MALDI imaging and profiling MS of higher mass proteins from tissue

Remoortere

Zeijl

Oever

et al. 2010

Self Cite

113

MALDI imaging and profiling mass spectrometry of proteins typically leads to the detection of a large number of peptides and small proteins but is much less successful for larger proteins: most ion signals correspond to proteins of m/z Ͻ 25,000. This is a severe limitation as many proteins, including cytokines, growth factors, enzymes, and receptors have molecular weights exceeding 25 kDa. The detector technology typically used for protein imaging, a microchannel plate, is not well suited to the detection of high m/z ions and is prone to detector saturation when analyzing complex mixtures. Here we report increased sensitivity for higher mass proteins by using the CovalX high mass HM1 detector (Zurich, Switzerland), which has been specifically designed for the detection of high mass ions and which is much less prone to detector saturation. The results demonstrate that a range of different sample preparation strategies enable higher mass proteins to be analyzed if the detector technology maintains high detection efficiency throughout the mass range. The detector enables proteins up to 70 kDa to be imaged, and proteins up to 110 kDa to be detected, directly from tissue, and indicates new directions by which the mass range amenable to MALDI imaging MS and MALDI profiling MS may be extended. (J Am Soc Mass Spectrom 2010, 21, 1922-1929) © 2010 American Society for Mass Spectrometry S ince its inception ϳ10 y ago, MALDI imaging mass spectrometry (imaging MS) has developed into a powerful and versatile tool for biomedical research [1,2]. It is now routinely used for analyzing peptides and small proteins up to 25 kDa [3-6], administered drugs and their metabolites [7], and recently major improvements have been reported for lipids [8]. Despite this success, proteins exceeding 25 kDa are not routinely detected. Proteins larger than 25 kDa include many proteins with important biological activities, such as most cytokines, growth factors, enzymes, receptors, proproteins, and neuropeptide precursors. Increasing the mass range of proteins amenable to MALDI imaging MS might enable these biologically crucial proteins to be included in current applications, e.g., biomarker discovery.The most common technique currently used to access larger proteins in MALDI imaging MS analyses is based on proteolytic digestion of the tissue's proteins followed by MALDI imaging MS of their tryptic peptides. Note on-tissue digestion has the additional advantage that it can be applied to formalin fixed tissues as proteolytic peptides can be generated that are not bound within the cross-linked protein matrix. For example, Djidja et al. used on-tissue digestion to determine that the 78 kDa protein GRP78 may be a new candidate protein biomarker of pancreatic adenocarcinoma [9]. In principal, this 'bottom-up' strategy could enable proteins of any mass to be detected. In practice the large increase in complexity associated with proteolysing the entire tissue's protein content will cause many tryptic peptides to have identical nominal mass [1], thus under...

“…We demonstrate that this algorithm provides superior alignment performance than manual stitching and can be used to automatically align large imaging mass spectrometry datasets comprising many individual mosaic tiles. (J Am Soc Mass Spectrom 2008, 19, 823-832) © 2008 American Society for Mass Spectrometry I maging mass spectrometry is a rapidly developing analytical tool because it provides the ability to map the profiles of specific biomolecules, in which the intrinsic mass of the molecule differentiates between any modified forms; to record the distributions of multiple analytes in parallel; and to perform these analyses without a label and with clinical samples [1]. This combination of specificity, parallel detection, and non-targeted analysis has led to great excitement for its potential as a discovery tool.…”

mentioning

confidence: 99%

“…Recent advances in both ionization efficiency (polyatomic primary ions) and sample preparation have significantly improved the sensitivity for detecting intact, medium-sized molecular ions (Ͻ1000 Da) from tissues and cells [1][2][3][4][5][6]. High-resolution images of small peptides, lipids, cholesterol, vitamins, and pharmaceuticals have all been reported, and through the use of large polyatomic primary ions three-dimensional (3D) molecular imaging results are beginning to appear [7][8][9].…”

mentioning

confidence: 99%

Automated, feature-based image alignment for high-resolution imaging mass spectrometry of large biological samples

Broersen

Liere

Altelaar

et al. 2008

Self Cite

High-resolution imaging mass spectrometry of large biological samples is the goal of several research groups. In mosaic imaging, the most common method, the large sample is divided into a mosaic of small areas that are then analyzed with high resolution. Here we present an automated alignment routine that uses principal component analysis to reduce the uncorrelated noise in the imaging datasets, which previously obstructed automated image alignment. An additional signal quality metric ensures that only those regions with sufficient signal quality are considered. We demonstrate that this algorithm provides superior alignment performance than manual stitching and can be used to automatically align large imaging mass spectrometry datasets comprising many individual mosaic tiles. (J Am Soc Mass Spectrom 2008, 19, 823-832) © 2008 American Society for Mass Spectrometry I maging mass spectrometry is a rapidly developing analytical tool because it provides the ability to map the profiles of specific biomolecules, in which the intrinsic mass of the molecule differentiates between any modified forms; to record the distributions of multiple analytes in parallel; and to perform these analyses without a label and with clinical samples [1]. This combination of specificity, parallel detection, and non-targeted analysis has led to great excitement for its potential as a discovery tool.It is the goal of many research groups to be able to perform high-resolution analysis of large samples, thus combining the ability to examine distributions between organs/tumors and their surroundings as well as to investigate the subcellular/intracellular locations of the biomolecules. The central premise of this approach is that the subcellular locations will provide some of the information required to explain differences in the more global patterns.High spatial resolution measurements are a wellestablished ability of secondary ion mass spectrometry (SIMS). Recent advances in both ionization efficiency (polyatomic primary ions) and sample preparation have significantly improved the sensitivity for detecting intact, medium-sized molecular ions (Ͻ1000 Da) from tissues and cells [1][2][3][4][5][6]. High-resolution images of small peptides, lipids, cholesterol, vitamins, and pharmaceuticals have all been reported, and through the use of large polyatomic primary ions three-dimensional (3D) molecular imaging results are beginning to appear [7][8][9].The images are normally created by moving the ionization beam in a set pattern across the sample and performing mass analysis at each point of the raster (spatially correlated mass spectrometry). The raster pattern typically uses 8-or 10-bit encoding; as a result the maximum analysis field contains 256 ϫ 256 (or 1024 ϫ 1024) pixels. In a typical high spatial resolution SIMS measurement the pixel size is about 200 nm, meaning maximum analysis areas of approximately 50 or 200 m, respectively. This is much smaller than many of the biological samples of interest; for example, a tissue section of an adult rat ...