Detection of fatty acids from intact microorganisms by molecular beam static secondary ion mass spectrometry

Determination of Pathogens by Electrophoretic and Spectrometric Techniques

In modern medical diagnostics, where analytical chemistry plays a key role, fast and accurate identification of pathogens is becoming increasingly important. Infectious diseases pose a growing threat to public health due to population growth, international air travel, bacterial resistance to antibiotics, and other factors. For instance, the detection of SARS-CoV-2 in patient samples is a key tool to monitor the spread of the disease. While there are several techniques for identifying pathogens by their genetic code, most of these methods are too expensive or slow to effectively analyze clinical and environmental samples that may contain hundreds or even thousands of different microbes. Standard approaches (e.g., culture media and biochemical assays) are known to be very time- and labor-intensive. The purpose of this review paper is to highlight the problems associated with the analysis and identification of pathogens that cause many serious infections. Special attention was paid to the description of mechanisms and the explanation of the phenomena and processes occurring on the surface of pathogens as biocolloids (charge distribution). This review also highlights the importance of electromigration techniques and demonstrates their potential for pathogen pre-separation and fractionation and demonstrates the use of spectrometric methods, such as MALDI-TOF MS, for their detection and identification.

In situ molecular imaging of a hydrated biofilm in a microfluidic reactor by ToF-SIMS

A novel microfluidic reactor for biofilm growth was constructed to enablein situchemical imaging of hydrated biofilms using ToF-SIMS.

Image and Spectral Processing for ToF-SIMS Analysis of Biological Materials

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) instruments can rapidly produce large complex data sets. Within each spectrum, there can be hundreds of peaks. A typical 256×256 pixel image contains 65,536 spectra. If this is extended to a 3D image, the number of spectra in a given data set can reach the millions. The challenge becomes how to process these large data sets while taking into account the changes and differences between all the peaks in the spectra. This is particularly challenging for biological materials that all contain the same types of proteins and lipids, just in varying concentrations and spatial distributions. This data analysis challenge is further complicated by the limitations in the ion yield of higher mass, more chemically specific species, and potentially by the processing power of typical computers. Herein we briefly discuss analysis methodologies including univariate analysis, multivariate analysis (MVA) methods, and some of the limitations of ToF-SIMS analysis of biological materials.

Multivariate analysis of ToF-SIMS data from multicomponent systems: the why, when, and how

The use of multivariate analysis (MVA) methods in the processing of time-of-flight secondary ion mass spectrometry (ToF-SIMS) data has become increasingly more common. MVA presents a powerful set of tools to aid the user in processing data from complex, multicomponent surfaces such as biological materials and biosensors. When properly used, MVA can help the user identify the major sources of differences within a sample or between samples, determine where certain compounds exist on a sample, or verify the presence of compounds that have been engineered into the surface. Of all the MVA methods, principal component analysis (PCA) is the most commonly used and forms an excellent starting point for the application of many of the other methods employed to process ToF-SIMS data. Herein we discuss the application of PCA and other MVA methods to multicomponent ToF-SIMS data and provide guidelines on their application and use.

Enhanced detection of olefins using ambient ionization mass spectrometry: Ag+ adducts of biologically relevant alkenes

Spray solvent doped with silver ions increases the ease of olefin detection by desorption electrospray ionization (DESI). Characteristic silver adducts were generated in up to 50 times greater abundance when compared to conventional DESI spray solvents for the biologically significant olefin, arachidonic acid, in the positive ion mode. In the analysis of 26 lipids, silver adduct formation was highly favorable for fatty acids, fatty acid esters and prostaglandins but not applicable to some other classes (e.g., polar lipids such as ceramide and its derivative cerebroside sulfate). An investigation exploring competitive Ag(+) cationization with a mixture of components demonstrated that polyunsaturated compounds form Ag(+) adducts most readily. Silver cationization allowed the distinction between three sets of isomers in the course of multiple-stage collision-induced dissociation, so providing insight into the location of the olefin bonds. A silver ion-doped solvent was used in DESI imaging of normal and tumor canine bladder tissue sections. The Ag(+) fatty acid adducts permitted post facto differentiation between the normal and tumor regions. In addition, silver adduct formation in the course of DESI imaging of tissue sections revealed the presence of triacylglycerides, a class of compounds not previously identified through DESI imaging. A simple silver nitrate spray solvent has the potential to further improve DESI analysis of unsaturated biomolecules and other molecules containing π-bonds through selective silver cationization.

Chapter 13: Imaging of cells and tissues with mass spectrometry: adding chemical information to imaging

Techniques that map the distribution of compounds in biological tissues can be invaluable in addressing a number of critical questions in biology and medicine. One of the newer methods, mass spectrometric imaging, has enabled investigation of spatial localization for a variety of compounds ranging from atomics to proteins. The ability of mass spectrometry to detect and differentiate a large number of unlabeled compounds makes the approach amenable to the study of complex biological tissues. This chapter focuses on recent advances in the instrumentation and sample preparation protocols that make mass spectrometric imaging of biological samples possible, including strategies for both tissue and single-cell imaging using the following mass spectrometric ionization methods: matrix-assisted laser desorption/ionization, secondary ion, electrospray, and desorption electrospray.

Application of TOF-SIMS with chemometrics to discriminate between four different yeast strains from the species Candida glabrata and Saccharomyces cerevisiae

We present a TOF-SIMS analysis of the cell surface differences between four yeast strains from two species, Candida glabrata and Saccharomyces cerevisiae (haploid strains BY4742 and BY4741 and the derived diploid BY4743). The study assesses the suitability of TOF-SIMS analysis in combination with statistical methods (principal component analysis, Fisher's discriminant analysis, and cluster analysis) for the discrimination between the four yeast strains. We demonstrate that a combination of these statistical methods identifies 34 ions, from a total data set of 1200, which can be used to distinguish between the four yeasts. The study discusses the assignments of surface cell membrane phospholipids for the identified ions and the resulting differences in the phospholipid pattern between the four yeasts, particularly in relation to ploidy and budding pattern. The method shows that fatty acids, phosphatidylglycerols, phosphatidylethanolamines, phosphatidylserines, and phosphatidylcholines, as well as cardiolipins, are of diagnostic importance.

Spatially-correlated mass spectrometric analysis of microbe–mineral interactions

A new methodology for examining the interactions of microbes with heterogeneous minerals is presented. Imaging laser desorption Fourier transform mass spectrometry was used to examine the colonization patterns of Burkholderia vietnamiensis G4 (previously Burkholderia cepacia G4) on a heterogeneous basalt sample. Depth-profile imaging found that the bacterium preferentially colonized the plagioclase mineral phase within the basalt.

Strategies and data analysis techniques for lipid and phospholipid chemistry elucidation by intact cell MALDI-FTMS

Ions attributed to lipids and phospholipids are directly observed by desorption from whole bacteria using intact cell (IC) matrix-assisted laser desorption-ionization (MALDI) Fourier transform mass spectrometry (FTMS). Saccharomyces cerevisiae are grown in rich media broth, concentrated, and applied directly to the MALDI surface without lysis or chemical treatment. FTMS of MALDI ions gives excellent signal to noise ratios with typical resolving powers of 90,000 and mass precision better than 0.002 Da. Use of accurate mass measurements and a simple set of rules allow assignment of major peaks into one of twelve expected lipid classes. Subsequently, fractional mass versus whole number mass plots are employed to enhance visual interpretation of the high-resolution data and to facilitate detection of related ions such as those representing homologous series or different degrees of unsaturation. This approach, coupled with rules based on bacterial biochemistry, is used to classify ions with m/z up to about 1000. Major spectral peaks in the range m/z 200-1000 are assigned as lipids and phospholipids. In this study, it is assumed that biologically-derived ions with m/z values lower than 1000 are lipids. This is not unreasonable in view of the facts that molecular weights of lipids are almost always less than 1000 Da, that the copy numbers for lipids in a cell are higher than those for any single protein or other component, and that lipids are generally collections of distinct homologous partners, unlike proteins or other cell components. This paper presents a new rapid lipid-profiling method based on IC MALDI-FTMS.

Imaging Secondary Ion Mass Spectrometry of a Paint Cross Section Taken from an Early Netherlandish Painting by Rogier van der Weyden

Static secondary ion mass spectrometry (SIMS) is introduced as an analytical technique for the examination of paint cross sections to obtain simultaneous information about the nature and distribution of pigments and the binding medium from a single sample. A sample taken from the virgin's blue robe in the panel painting The Descent from the Cross (Museo del Prado, Madrid) of the Early Netherlandish painter Rogier van der Weyden (1399/1400-1464) was selected for investigation. Data were compared with reference compounds and reference lead white linseed oil paint and egg tempera paint. The static SIMS technique gave position-sensitive mass spectra that were used to image the elemental distribution of pigments and the molecular signature of components of the oleaginous binding medium. SIMS ion images of sodium and aluminum superimposed with the blue pigment ultramarine and those of copper, lead, and calcium with the position of the mineral pigments of azurite, lead white, and chalk, respectively. Preserved monocarboxylic acids of palmitic and stearic acids present as fatty acids and fatty acid lead soaps pointed to the use of linseed oil as a binding medium. Images from the oleaginous binding medium fatty acids show a correlation with the three main paint layers. The observed palmitic/stearic acid ratios for the two ultramarine layers and azurite layers are 1.3, 1.4, and 1.8, respectively. Fatty acids and fatty acid soaps show highest ion yields near lead white, a mineral pigment that serves as a natural chemical drier and is proposed to act as a template for the initial grafting of the polyunsaturated triglycerides of the linseed oil. Almost no fatty acids were detected in other layers visible by light microscopy. The fatty acid lead soaps point toward a mature ionomeric oil paint system that developed over centuries. SIMS evidence for egg tempera, still used in the 15th century, is not detected in the paint cross section. SIMS images correlate well with SEM/EDX, FT-IR and light microscopic images and the SIMS spectral data additionally support the identification of pigment particles, lead soaps, and other binding medium components.