Characterizing chemical changes within individual cells is important for determining fundamental mechanisms of biological processes that will lead to new biological insights and improved disease understanding. Analyzing biological systems with imaging and profiling mass spectrometry (MS) has gained popularity in recent years as a method for creating chemical maps of biological samples. To obtain mass spectra that provide relevant molecular information about individual cells, samples must be prepared so that salts and other cell culture components are removed from the cell surface and that the cell contents are rendered accessible to the desorption beam. We have designed a cellular preparation protocol for imaging/profiling MS that removes the majority of the interfering species derived from the cellular growth medium, preserves the basic morphology of the cells, and allows chemical profiling of the diffusible elements of the cytosol. Using this method, we are able to reproducibly analyze cells from three diverse cell types: MCF7 human breast cancer cells, Madin-Darby canine kidney (MDCK) cells, and NIH/3T3 mouse fibroblasts. This preparation technique makes possible routine imaging/profiling MS analysis of individual cultured cells, allowing for understanding of molecular processes within individual cells.

The stable isotopes of hydrogen (δ2H) and oxygen (δ18O) in human urine are measured during studies of total energy expenditure by the doubly labeled water method, measurement of total body water, and measurement of insulin resistance by glucose disposal among other applications. An ultrasensitive laser absorption spectrometer based on off-axis integrated cavity output spectroscopy was demonstrated for simple and inexpensive measurement of stable isotopes in natural isotopic abundance and isotopically enriched human urine. Preparation of urine for analysis was simple and rapid (approx. 25 samples per hour), requiring no decolorizing or distillation steps. Analysis schemes were demonstrated to address sample-to-sample memory while still allowing analysis of 45 natural or 30 enriched urine samples per day. The instrument was linear over a wide range of water isotopes (δ2H = −454 to +1702 ‰ and δ18O= −58.3 to +265 ‰). Measurements of human urine were precise to better than 0.65 ‰ 1σ for δ2H and 0.09 ‰ 1σ for δ18O for natural urines, 1.1 ‰ 1σ for δ2H and 0.13 ‰ 1σ for δ18O for low enriched urines, and 1.0 ‰ 1σ for δ2H and 0.08 ‰ 1σ for δ18O for high enriched urines. Furthermore, the accuracy of the isotope measurements of human urines was verified to better than ±0.81 ‰ in δ2H and ±0.13 ‰ in δ18O (average deviation) against three independent IRMS laboratories. The ability to immediately and inexpensively measure the stable isotopes of water in human urine is expected to increase the number and variety of experiments which can be undertaken.

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Characterizing and classifying molecular variations within biological samples are critical for determining the fundamental mechanisms of biological processes. Toward these ends, time-of-flight secondary ion mass spectrometry (ToF-SIMS) was used to examine increasingly complex samples of biological relevance. The large, multivariate datasets were analyzed using five common statistical and chemometric techniques: principal component analysis (PCA), linear discriminant analysis (LDA), partial least-squares discriminant analysis (PLSDA), soft independent modeling of class analogy (SIMCA), and decision-tree analysis by recursive partitioning. PCA was found to provide insight into both the relative groupings of samples and the molecular basis for those groupings. For monosaccharide, pure protein, and complex protein mixture samples, LDA, PLSDA, and SIMCA all produced excellent classification. For mouse embryo tissues, however, SIMCA did not classify samples as accurately. The decision-tree analysis was the least successful for all tested samples, providing neither as accurate a classification nor chemical insight. Based on these results we conclude that as the complexity of samples increases, so must the sophistication of the multivariate technique used to classify the samples. PCA is a preferred first step for understanding ToF-SIMS data that can be followed by either LDA or PLSDA for effective classification. This study demonstrates the strength of the combination of ToF-SIMS and multivariate analysis to classify increasingly complex biological samples. Applying these techniques to information-rich mass spectral data opens the possibilities for new applications including classification of subtly different biological samples that may provide insights into cellular processes, disease progress, and disease diagnosis.

Characterizing chemical changes within single cells is important for determining fundamental mechanisms of biological processes that will lead to new biological insights and improved disease understanding. Imaging biological systems with mass spectrometry (MS) has gained popularity in recent years as a method for creating precise chemical maps of biological samples.In order to obtain high-quality mass spectral images that provide relevant molecular information about individual cells, samples must be prepared so that salts and other cell-culture components are removed from the cell surface and the cell contents are rendered accessible to the desorption beam. We have designed a cellular preparation protocol for imaging MS that preserves the cellular contents for investigation and removes the majority of the interfering species from the extracellular matrix. Using this method, we obtain excellent imaging results and reproducibility in three diverse cell types: MCF7 human breast cancer cells, Madin-Darby canine kidney (MDCK) cells, and NIH/3T3 mouse fibroblasts. This preparation technique allows routine imaging MS analysis of cultured cells, allowing for any number of experiments aimed at furthering scientific understanding of molecular processes within individual cells.