Zejian Huang

Data Processing for 3D Mass Spectrometry Imaging

Data processing for three dimensional mass spectrometry (3D-MS) imaging was investigated, starting with a consideration of the challenges in its practical implementation using a series of sections of a tissue volume. The technical issues related to data reduction, 2D imaging data alignment, 3D visualization, and statistical data analysis were identified. Software solutions for these tasks were developed using functions in MATLAB. Peak detection and peak alignment were applied to reduce the data size, while retaining the mass accuracy. The main morphologic features of tissue sections were extracted using a classification method for data alignment. Data insertion was performed to construct a 3D data set with spectral information that can be used for generating 3D views and for data analysis. The imaging data previously obtained for a mouse brain using desorption electrospray ionization mass spectrometry (DESI-MS) imaging have been used to test and demonstrate the new methodology.

Development and Characterizations of a Miniature Capillary Electrophoresis Mass Spectrometry System

A miniature capillary electrophoresis mass spectrometry (CE/MS) system has been developed in this work. A 100% electrical driven miniaturized CE device was integrated with a miniature MS instrument, which has a discontinuous atmospheric pressure interface (DAPI) for coupling with atmospheric pressure ionization sources. A nanoelectrospray ionization (nano-ESI) source was developed with a sheath liquid interface for coupling the miniature CE and the MS system. A systematic characterization and optimization of the analytical performance have been done. The analysis of isobaric peptides and avoiding charge competition effects in nano-ESI sources have been demonstrated.

The coupling effects of hexapole and octopole fields in quadrupole ion traps: a theoretical study

A theoretical method, the harmonic balance method, was introduced to study the coupling effects of hexapole and octopole fields on ion motion in a quadrupole ion trap. Ion motion characteristics, such as ion motion center displacement, ion secular frequency shift, nonlinear resonance curve and buffer gas damping effects, have been studied with the presence of both hexapole and octopole fields. It is found that hexapole fields have bigger impacts on ion motion center displacement, while octopole fields dominate ion secular frequency shift. Furthermore, the nonlinear features originated from hexapole and octopole fields could enhance or cancel each other, which provide us more space in a practical ion trap design process. As an example, an ion trap with improved performance was designed using a specific combination of hexapole and octopole fields. In this ion trap, a hexapole field was used to achieve efficient ion directional ejection, while an octopole field was added to correct the chemical mass shift and resolution degradation introduced by the hexapole field.

Feature Extraction Approach for Mass Spectrometry Imaging Data Using Non-negative Matrix Factorization

Abstract Mass spectrometry imaging (MSI) provides molecules composition information and corresponding spatial information on complex biological surfaces in a single experiment without label. It is a hotspot for getting significant amount of attention in the mass spectrometric community currently. However, the MSI data are large and complexity, which makes the reduction and feature extraction difficult. Some multivariate statistical analysis methods, for example, the famous principal component analysis (PCA), were developed to address this issue. But the results with negative value are hard to be interpreted as features about molecules. In this study, a feature extraction approach for MSI data by applying non-negative matrix factorization was developed. It could extract single molecules composition feature and corresponding distribution (basic images) feature, and further integrated the basic images to create a profile showing the whole sample by RGB (red, green and blue) color overlaid model clearly. The MSI data of a mouse brain section was used to test the efficiency of this approach. The white matter regions, the grey matter regions and the background regions were clearly observed and the corresponding molecules mass spectrums were extracted, which indicated that the approach was easier than PCA approach in results interpreting. Moreover, the MSI data of a human cancerous and adjacent normal bladder tissue sections on the same sample target were analyzed by the approach, and the cancerous regions and the normal regions were clearly differentiated. The software developed in this paper could be downloaded from the website http://www.msimaging.net .

Certified reference materials (GBW09170 and 09171) of creatinine in human serum

Creatinine is the most widely used clinical marker for assessing renal function. Concentrations of creatinine in human serum need to be carefully checked in order to ensure accurate diagnosis of renal function. Therefore, development of certified reference materials (CRMs) of creatinine in serum is of increasing importance. In this study, two new CRMs (Nos. GBW09170 and 09171) for creatinine in human serum have been developed. They were prepared with mixtures of several dozens of healthy peoples and kidney disease patients serum, respectively. The certified values of 8.10, 34.1 mg/kg for these two CRMs have been assigned by liquid chromatography-isotope dilution mass spectrometry (LC-IDMS) method which was validated by using standard reference material (SRM) of SRM909b (a reference material obtained from National Institute of Standards and Technology, NIST). The expanded uncertainties of certified values for low and high concentrations were estimated to be 1.2 and 1.1%, respectively. The certified values were further confirmed by an international intercomparison for the determination of creatinine in human serum (Consultative Committee for Amount of Substance, CCQM) of K80 (CCQM-K80). These new CRMs of creatinine in human serum pool are totally native without additional creatinine spiked for enrichment. These new CRMs are capable of validating routine clinical methods for ensuring accuracy, reliability and comparability of analytical results from different clinical laboratories. They can also be used for instrument validation, development of secondary reference materials, and evaluating the accuracy of high order clinical methods for the determination of creatinine in human serum.

Artificial Neural Networks for Classification and Identification of Data of Biological Tissue Obtained by Mass-Spectrometry Imaging

Abstract Mass-spectrometry imaging (MSI), the combination of molecular mass analysis and spatial information, providing visualization of molecules on complex biological surfaces, is currently receiving a significant amount of attention among the mass-spectrometry community. One important problem in this research field concerns the development of an effective method for the classification and identification of MSI data, especially for both differentiating a cancerous tissue from adjacent normal tissues and classifying the different functional regions in a complex biological tissue. For this purpose, we developed a new method, which involved image reconstruction from raw mass-spectral data; preprocessing of MSI data; classification of tissue regions with reference to the background regions using self-organizing feature maps; and identification of regions of special interest in whole-tissue samples by learning-vector quantization. The MSI data of samples of six pairs (12 tissue samples) of human cancerous and adjacent normal bladder tissues were used to test the efficacy of this method. The results showed an error rate of less than 23.38% for identification of cancerous regions and an error rate of less than 9.08% for identification of the adjacent normal regions. The method was also tested with reference to classification of the regions of the white matter and gray matter of three adjacent slices of mouse brain tissue. The slice in the middle was used to establish an identification model, and the other two slices were used to test the model. The inconsistency rate of the results obtained by identification using a self-organizing feature map was less than 4% compared with the results using learning-vector quantization. This indicated that the method could be carried out simply and efficiently to extend the capability of MSI and underlined its potential to be a regular tool in the studies related to clinical applications.

Ultrasensitive analysis of heat shock protein 90α with antibodies orderly arrayed on a novel type of immunoprobe based on magnetic COFs

The early diagnosis of liver cancer by target biomarkers is of great significance for improving the survival rate of cancer patients. However, it is still a challenging task to sensitively detect circulating protein biomarkers due to decreased binding activity of antibodies originating from uncontrolled orientation of immobilization on the surface of a solid matrix. In this work, a novel immunoaffinity probe, Fe3O4@TpBD-DSS-Ab-MEG, based on magnetic COFs with ordered arrangement of anchored antibodies has been developed and applied for the first time to detection of a cancer biomarker, heat shock protein 90alpha (Hsp90α). The fabricated composites possess favorable features from magnetic cores and COF shells, including strong magnetic responses (7.96 emu g-1), ordered active groups, a large amount of immobilized antibodies (111.7 μg/mg), good solvent and thermal stability. Fe3O4@TpBD-DSS-Ab-MEG demonstrated low detection limit (50 pg/mL), high selectivity (Hsp90α:BSA = 1:1000), desirable repeatability and good stability for Hsp90α immunocapture. Compared with other immunoprobes, our materials showed higher selectivity and sensitivity, which were mainly attributed to regular arrays of surface antibodies. Furthermore, samples containing Hsp90α at the concentration of 1 µg/mL in human plasma were used to test our immunoprobe, and 2 peptides of Hsp90α were successfully observed. The proposed non-invasive immunoassay strategy offers enhanced ability to control the orientation of immobilized antibodies and great promise for accurate analysis of the liver cancer biomarker Hsp90α in a complicated biological matrix. In addition, the facile preparation of magnetic COFs support and the satisfactory analytical performance made the newly developed immunoprobe a potential tool for sensitive detection of other cancer biomarkers in clinical diagnosis.