ABSTRACT
As a promising new molecular imaging technique,mass spectrometry imaging(MSI) has attracted more and more attention in the field of biomedicine. A method of air flow assisted ionization-ultra high resolution mass spectrometry-based mass spectrometric imaging (AFAI-MSI) was developed to profile endogenous metabolites in rat kidney tissue in this study. Rat kidneys were collected and cut into frozen tissue sections,and then were analyzed on an AFAI-MSI system in positive ion mode using acetonitrile-isopmpyl alcohol-water (4:4:2,V/V,5 μL/min) as spray solvent,N2as spray gas(0.6 MPa) and air as assisting gas (45 L/min). The mass range and resolution were set to be 70-1000 Da and 70000, respectively. As a result,a total of 38 metabolites, including organic amines, sugars, vitamins, peptides, neurotransmitters, organic acids,phospholipids,sphingolipids,glyceride,and cholesterol esters, were identified and imaged to characterize their tissue-specific distribution in kidney tissues, and some metabolites, such as choline, acetylcoline,betaine,phoshocholine,and glycerophosphocholine were found to have distinct distribution along the cortex-medulla axis,which may be involved in the formation of osmotic pressure gradient in the kidney. The proposed ultra high resolution mass spectrometry based AFAI-MSI method could work without sample pretreatment, showed high sensitivity and wide metabolite coverage, and was expected to provide a new analytical approach for the research of in situ characterization and metabolic regulation mechanism of endogenous metabolites in kidney.
ABSTRACT
The factor analysis method applied in imaging mass spectrometry data analysis was studied. The imaging mass spectrometric data were obtained by air flow-assisted ionization imaging mass spectrometry method. The sample contained some symbols which were drawn on slides using three different inks ( red, blue, black) . The imaging data analyzed by factor analysis method were divided into the background, black, blue and red factor. The results showed that the scores of m/z=443. 2, 478. 4, 322. 2(344. 2) in red, blue, black factor respectively were much larger than others. Therefore, they were markers of three inks. The results accorded with actual condition well and proved that the application of factor analysis in imaging mass spectrometric data analysis was feasible. The data analysis results of factor analysis and principal component analysis were compared. The results showed that the target sample markers could be extracted by factor analysis simply and quantitatively. It was of great potential in biomarker extraction, diseases diagnose and pharmacological analysis.