Discriminating and Imaging Different Phosphatidylcholine Species within Phase-Separated Model Membranes by Principal Component Analysis of TOF-Secondary Ion Mass Spectrometry Images

Applications of multivariate analysis and unsupervised machine learning to ToF-SIMS images of organic, bioorganic, and biological systems

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging offers a powerful, label-free method for exploring organic, bioorganic, and biological systems. The technique is capable of very high spatial resolution, while also producing an enormous amount of information about the chemical and molecular composition of a surface. However, this information is inherently complex, making interpretation and analysis of the vast amount of data produced by a single ToF-SIMS experiment a considerable challenge. Much research over the past few decades has focused on the application and development of multivariate analysis (MVA) and machine learning (ML) techniques that find meaningful patterns and relationships in these datasets. Here, we review the unsupervised algorithms—that is, algorithms that do not require ground truth labels—that have been applied to ToF-SIMS images, as well as other algorithms and approaches that have been used in the broader family of mass spectrometry imaging (MSI) techniques. We first give a nontechnical overview of several commonly used classes of unsupervised algorithms, such as matrix factorization, clustering, and nonlinear dimensionality reduction. We then review the application of unsupervised algorithms to various organic, bioorganic, and biological systems including cells and tissues, organic films, residues and coatings, and spatially structured systems such as polymer microarrays. We then cover several novel algorithms employed for other MSI techniques that have received little attention from ToF-SIMS imaging researchers. We conclude with a brief outline of potential future directions for the application of MVA and ML algorithms to ToF-SIMS images.

Unveiling microbial preservation under hyperacidic and oxidizing conditions in the Oligocene Rio Tinto deposit

The preservation of biosignatures on Mars is largely associated with extensive deposits of clays formed under mild early Noachian conditions (> 3.9 Ga). They were followed by widespread precipitation of acidic sulfates considered adverse for biomolecule preservation. In this paper, an exhaustive mass spectrometry investigation of ferric subsurface materials in the Rio Tinto gossan deposit (~ 25 Ma) provides evidence of well-preserved molecular biosignatures under oxidative and acidic conditions. Time of flight secondary ion mass spectrometry (ToF–SIMS) analysis shows a direct association between physical-templating biological structures and molecular biosignatures. This relation implies that the quality of molecular preservation is exceptional and provides information on microbial life formerly operating in the shallow regions of the Rio Tinto subsurface. Consequently, low-pH oxidative environments on Mars could also record molecular information about ancient life in the same way as the Noachian clay-rich deposits.

Screening of important metabolites and KRAS genotypes in colon cancer using secondary ion mass spectrometry

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) is an imaging-based analytical technique that can characterize the surfaces of biomaterials. We used TOF-SIMS to identify important metabolites and oncogenic KRAS mutation expressed in human colorectal cancer (CRC). We obtained 540 TOF-SIMS spectra from 180 tissue samples by scanning cryo-sections and selected discriminatory molecules using the support vector machine (SVM) algorithm. Each TOF-SIMS spectrum contained nearly 860,000 ion profiles and hundreds of spectra were analyzed; therefore, reducing the dimensionality of the original data was necessary. We performed principal component analysis after preprocessing the spectral data, and the principal components (20) of each spectrum were used as the inputs of the SVM algorithm using the R package. The performance of the algorithm was evaluated using the receiver operating characteristic (ROC) area under the curve (AUC) (0.9297). Spectral peaks (m/z) corresponding to discriminatory molecules used to classify normal and tumor samples were selected according to p-value and were assigned to arginine, α-tocopherol, and fragments of glycerophosphocholine. Pathway analysis using these discriminatory molecules showed that they were involved in gastrointestinal disease and organismal abnormalities. In addition, spectra were classified according to the expression of KRAS somatic mutation, with 0.9921 AUC. Taken together, TOF-SIMS efficiently and simultaneously screened metabolite biomarkers and performed KRAS genotyping. In addition, a machine learning algorithm was provided as a diagnostic tool applied to spectral data acquired from clinical samples prepared as frozen tissue slides, which are commonly used in a variety of biomedical tests.

Understanding mass spectrometry images: complexity to clarity with machine learning

The application of artificial intelligence and machine learning to hyperspectral mass spectrometry imaging (MSI) data has received considerable attention over recent years. Various methodologies have shown great promise in their ability to handle the complexity and size of MSI data sets. Advances in this area have been particularly appealing for MSI of biological samples, which typically produce highly complicated data with often subtle relationships between features. There are many different machine learning approaches that have been applied to MSI data over the past two decades. In this review, we focus on a subset of non-linear machine learning techniques that have mostly only been applied in the past 5 years. Specifically, we review the use of the self-organizing map (SOM), SOM with relational perspective mapping (SOM-RPM), t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP). While not their only functionality, we have grouped these techniques based on their ability to produce what we refer to as similarity maps. Similarity maps are color representations of hyperspectral data, in which spectral similarity between pixels-that is, their distance in high-dimensional space-is represented by relative color similarity. In discussing these techniques, we describe, briefly, their associated algorithms and functionalities, and also outline applications in MSI research with a strong focus on biological sample types. The aim of this review is therefore to introduce this relatively recent paradigm for visualizing and exploring hyperspectral MSI, while also providing a comparison between each technique discussed.

Investigation of heart lipid changes in acute β-AR activation-induced sudden cardiac death by time-of-flight secondary ion mass spectrometry

ToF-SIMS, PCA and PLS-DA were combined to compare lipid profiles of myocardial tissue in sudden cardiac death and normal, mice and humans. SIMS imaging was utilized to correlate the composition and structural changes.

An investigation of the beam damage effect on in situ liquid secondary ion mass spectrometry analysis

RATIONALE

During in situ liquid secondary ion mass spectrometry (SIMS) analysis, the primary ion beam is normally scanned on a very small area to collect signals with high ion doses (10¹⁴ to 10¹⁶ ions/cm² ). As a result, beam damage may become a concern when compared with the static limit of SIMS analysis, in which the dose is normally less than 10¹² ions/cm² . Therefore, a comparison of ion yields in in situ liquid SIMS analysis versus traditional static SIMS analysis of corresponding dry samples is of great interest.

METHODS

In this study, a dipalmitoylphosphatidylcholine (DPPC) liposome solution was used as a model system. Both liquid sample and dry sample were examined. Secondary ion yields using three primary ion species (Bi⁺ , Bi₃⁺ and Bi₃⁺⁺ ) with various beam currents were investigated.

RESULTS

Usable ion yields for both positive and negative characteristic signals (including molecular ions and characteristic fragment ions) were achievable based on optimized experimental conditions for in situ liquid SIMS analysis. The ion yield of the key DPPC molecular ion was comparable to that of traditional static SIMS, and unexpected low fragmentation was observed. The flexible structure of the liquid plays an important role for these observations.

CONCLUSIONS

Therefore, beam damage may not be a concern in in situ liquid SIMS analysis if proper experimental conditions are used.

Microscale Mass Spectrometry Analysis of Extracellular Metabolites in Live Multicellular Tumor Spheroids

Extracellular compounds in tumors play critical roles in intercellular communication, tumor proliferation, and cancer cell metastasis. However, the lack of appropriate techniques leads to limited studies of extracellular metabolite. Here, we introduced a microscale collection device, the Micro-funnel, fabricated from biocompatible fused silica capillary. With a small probe size (∼25 μm), the Micro-funnel can be implanted into live multicellular tumor spheroids to accumulate the extracellular metabolites produced by cancer cells. Metabolites collected in the Micro-funnel device were then extracted by a microscale sampling and ionization device, the Single-probe, for real-time mass spectrometry (MS) analysis. We successfully detected the abundance change of anticancer drug irinotecan and its metabolites inside spheroids treated under a series of conditions. Moreover, we found that irinotecan treatment dramatically altered the composition of extracellular compounds. Specifically, we observed the increased abundances of a large number of lipids, which are potentially related to the drug resistance of cancer cells. This study provides a novel way to detect the extracellular compounds inside live spheroids, and the successful development of our technique can benefit the research in multiple areas, including the microenvironment inside live tissues, cell-cell communication, biomarker discovery, and drug development.

Alteration of Membrane Compositional Asymmetry by LiCoO2 Nanosheets

Given the projected massive presence of redox-active nanomaterials in the next generation of consumer electronics and electric vehicle batteries, they are likely to eventually come in contact with cell membranes, with biological consequences that are currently not known. Here, we present nonlinear optical studies showing that lithium nickel manganese cobalt oxide nanosheets carrying a negative ζ-potential have no discernible consequences for lipid alignment and interleaflet composition in supported lipid bilayers formed from zwitterionic and negatively charged lipids. In contrast, lithiated and delithiated LiCoO2 nanosheets having positive and neutral ζ-potentials, respectively, alter the compositional asymmetry of the two membrane leaflets, and bilayer asymmetry remains disturbed even after rinsing. The insight that some cobalt oxide nanoformulations induce alterations to the compositional asymmetry in idealized model membranes may represent an important step toward assessing the biological consequences of their predicted widespread use.

Structural determinants of protein partitioning into ordered membrane domains and lipid rafts

Increasing evidence supports the existence of lateral nanoscopic lipid domains in plasma membranes, known as lipid rafts. These domains preferentially recruit membrane proteins and lipids to facilitate their interactions and thereby regulate transmembrane signaling and cellular homeostasis. The functionality of raft domains is intrinsically dependent on their selectivity for specific membrane components; however, while the physicochemical determinants of raft association for lipids are known, very few systematic studies have focused on the structural aspects that guide raft partitioning of proteins. In this review, we describe biophysical and thermodynamic aspects of raft-mimetic liquid ordered phases, focusing on those most relevant for protein partitioning. Further, we detail the variety of experimental models used to study protein-raft interactions. Finally, we review the existing literature on mechanisms for raft targeting, including lipid post-translational modifications, lipid binding, and transmembrane domain features. We conclude that while protein palmitoylation is a clear raft-targeting signal, few other general structural determinants for raft partitioning have been revealed, suggesting that many discoveries lie ahead in this burgeoning field.

Label-free characterization of biomembranes: from structure to dynamics

We review recent progress in the study of the structure and dynamics of phospholipid membranes and associated proteins, using novel label-free analytical tools. We describe these techniques and illustrate them with examples highlighting current capabilities and limitations. Recent advances in applying such techniques to biological and model membranes for biophysical studies and biosensing applications are presented, and future prospects are discussed.

Gemcitabine diphosphate choline is a major metabolite linked to the Kennedy pathway in pancreatic cancer models in vivo

BACKGROUND

The modest benefits of gemcitabine (dFdC) therapy in patients with pancreatic ductal adenocarcinoma (PDAC) are well documented, with drug delivery and metabolic lability cited as important contributing factors. We have used a mouse model of PDAC: KRAS(G12D); p53(R172H); pdx-Cre (KPC) that recapitulates the human disease to study dFdC intra-tumoural metabolism.

METHODS

LC-MS/MS and NMR were used to measure drug and physiological analytes. Cytotoxicity was assessed by the Sulphorhodamine B assay.

RESULTS

In KPC tumour tissue, we identified a new, Kennedy pathway-linked dFdC metabolite (gemcitabine diphosphate choline (GdPC)) present at equimolar amounts to its precursor, the accepted active metabolite gemcitabine triphosphate (dFdCTP). Utilising additional subcutaneous PDAC tumour models, we demonstrated an inverse correlation between GdPC/dFdCTP ratios and cytidine triphosphate (CTP). In tumour homogenates in vitro, CTP inhibited GdPC formation from dFdCTP, indicating competition between CTP and dFdCTP for CTP:phosphocholine cytidylyltransferase (CCT). As the structure of GdPC precludes entry into cells, potential cytotoxicity was assessed by stimulating CCT activity using linoleate in KPC cells in vitro, leading to increased GdPC concentration and synergistic growth inhibition after dFdC addition.

CONCLUSIONS

GdPC is an important element of the intra-tumoural dFdC metabolic pathway in vivo.

ToF-SIMS imaging of lipids and lipid related compounds in Drosophila brain

Drosophila melanogaster (fruit fly) has a relatively simple nervous system but possesses high order brain functions similar to humans. Therefore, it has been used as a common model system in biological studies, particularly drug addiction. Here, the spatial distribution of biomolecules in the brain of the fly was studied using time-of flight secondary ion mass spectrometry (ToF-SIMS). Fly brains were analyzed frozen to prevent molecular redistribution prior to analysis. Different molecules were found to distribute differently in the tissue, particularly the eye pigments, diacylglycerides, and phospholipids, and this is expected to be driven by their biological functions in the brain. Correlations in the localization of these molecules were also observed using principal components analysis of image data, and this was used to identify peaks for further analysis. Furthermore, consecutive analyses following 10 keV Ar₂₅₀₀⁺ sputtering showed that different biomolecules respond differently to Ar₂₅₀₀⁺ sputtering. Significant changes in signal intensities between consecutive analyses were observed for high mass molecules including lipids.

Imaging lipids with secondary ion mass spectrometry

This review discusses the application of time-of-flight secondary ion mass spectrometry (TOF-SIMS) and magnetic sector SIMS with high lateral resolution performed on a Cameca NanoSIMS 50(L) to imaging lipids. The similarities between the two SIMS approaches and the differences that impart them with complementary strengths are described, and various strategies for sample preparation and to optimize the quality of the SIMS data are presented. Recent reports that demonstrate the new insight into lipid biochemistry that can be acquired with SIMS are also highlighted. This article is part of a Special Issue entitled Tools to study lipid functions.

Characterization of sample preparation methods of NIH/3T3 fibroblasts for ToF-SIMS analysis

The information that is obtained from single cells during time-of-flight secondary ion mass spectrometry (ToF-SIMS) analysis is influenced by the method that was used to prepare the cells. The removal of extracellular media before analysis is necessary, but the rinsing technique should not damage the plasma membrane of the cell. The presence of intracellular salts reduced the secondary ion yield an average of 2.6-fold during Bi3 (+)/C60 (++) depth profiles. Chemical fixation followed by rinsing removed a majority of the intracellular salts, "recovering" the positive secondary ion yields. The formaldehyde-fixation process removed a majority of the intracellular Cl(-), but other key anions were not removed in significant amounts. The data presented here is consistent the anion neutralization mechanism largely responsible for the lower ion yields. All of the organic secondary ions that were detected in the freeze-dried cells were also detected in the formaldehyde-fixed cells, suggesting that the fixation process did not remove any molecular species to an extent that is detectable by ToF-SIMS. Compared to freeze dried cells, well preserved, frozen-hydrated cells showed little increase, or a decreased yield, for most low mass ions, but an increased yield for larger mass fragments. This is consistent with a reduced damage cross section at cryogenic analysis temperatures, although proton donation from water and reduction the salt effects in the presence of water likely also play roles. Numerous ions detected from the frozen-hydrated cells were not detected from the freeze dried cells, however many of these ions were attributed to chemical combinations of water, salts and the ammonium acetate rinsing solution.

A mass spectrometric study for comparative analysis and evaluation of metabolite recovery from plasma by various solvent systems

A solvent system that extracts a maximum number of metabolites belonging to diverse chemical classes from complex biofluids, such as plasma, may offer useful inputs to understand the metabolic and physiological state of an individual. The present study compared seven solvent systems for extraction of metabolites from plasma. The extracts were analyzed by mass spectrometry (MS) and MS/MS (MS2) using a quadrupole time-of-flight liquid chromatography/MS system in positive and negative modes of ionization. Metabolites with molecular mass below 400 were identified using Human Metabolome Database MS2 and MS search interfaces. The acetone/isopropanol (2:1) system yielded promising results in positive ionization mode, as the maximum number of MS and MS2 features was detected in the extract. It was found to be superior in extraction of various classes of metabolites, especially organic acids, nucleosides and nucleoside derivatives, and heterocyclic molecules. Glycerophosphocholines in the mass range of 400-700 were found to be efficiently extracted by the methanol/chloroform/water (8:1:1) system. In negative mode as well, the maximum number of MS2 features was detected in methanol/chloroform/water and acetone/isopropanol extracts. The fingerprints of molecular features obtained in the negative and positive modes differed from each other to a significant extent.

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.

Time-of-flight secondary ion mass spectrometry with principal component analysis of titania-blood plasma interfaces

Treatment of osseoimplant surfaces with autologous platelet-rich plasma prepared according to the plasma rich in growth factors (PRGF-Endoret) protocol prior to implantation yields promising results in the clinic. Our objective is to understand the organization of complex interfaces between blood plasma preparations of various compositions and model titania surfaces. Here we present the results of the morphological and chemical characterization of TiO(2) surfaces incubated with four types of blood plasma preparations devoid of leukocytes and red blood cells: either enriched in platelets (PRGF-Endoret) or platelet-depleted, and either activated with CaCl(2) to induce clotting, or not. Chemical characterization was done by time-of-flight secondary ion mass spectrometry with principal component analysis (ToF-SIMS/PCA). The interface morphology was studied with scanning electron and atomic force microscopy. Immunofluorescence microscopy was used to identify platelets and infer their activation state. We observe clear differences among the four types of interfaces by ToF-SIMS/PCA. Some of these could be straightforwardly related to the differences in the sample morphology and known effects of platelet activation, but others are more subtle. Strikingly, it was possible to differentiate between these samples by ToF-SIMS/PCA of the protein species alone. This clearly indicates that the composition, orientation, and/or conformation of the proteins in these specimens depend both on the platelets' presence and on their activation. The ToF-SIMS imaging functionality furthermore provides unique insight into the distribution of phospholipid species in these samples.

The effect of high vacuum on the mechanical properties and bioactivity of collagen fibril matrices

The extracellular matrix (ECM) environment plays a critical role in organism development and disease. Surface sensitive microscopy techniques for studying the structural and chemical properties of ECMs are often performed in high vacuum (HV) environments. In this report, we examine the affect HV conditions have on the bioactivity and mechanical properties of type I collagen fibrillar matrices. We find that HV exposure has an unappreciable affect on the cell spreading response and mechanical properties of these collagen fibril matrices. Conversely, low vacuum environments cause fibrils to become mechanically rigid as indicated by force microscopy, resulting in greater cell spreading. Time-of-flight secondary ion mass spectrometry results show no noticeable spectral differences between HV-treated and dehydrated matrices. While previous reports have shown that HV can denature proteins in monolayers, these observations indicate that HV-exposure does not mechanically or biochemically alter collagen in its supramolecular configuration. These results may have implication for complex ECM matrices such as decellularized scaffolds.

Secondary ion mass spectrometry imaging of biological membranes at high spatial resolution

Characterization of the distributions of specific proteins and lipids within cellular membranes is currently a major challenge. Advances in secondary ion mass spectrometry (SIMS) now enable the distributions of isotopically labeled lipids within cellular or model membranes to be imaged with chemical specificity and high (≥50 nm) lateral resolution. Here, methods to image the distributions of sphingolipids within the membranes of intact cells with a Cameca NanoSIMS are described. For NanoSIMS detection, the incorporation of distinct stable isotopes into the lipid species of interest is essential. Metabolic labeling, cell preservation, imaging conditions, and data analysis are critical factors. The methods and principles described here can be extended to studying other membrane lipids or cholesterol.

Quantifying the molar percentages of cholesterol in supported lipid membranes by time-of-flight secondary ion mass spectrometry and multivariate analysis

The uneven cholesterol distribution among organelles and within the plasma membrane is postulated to be critical for proper cellular function. To study how interactions between cholesterol and specific lipid species contribute to the uneven cholesterol distribution between and within cellular membranes, model lipid membranes are frequently employed. Although the cholesterol distributions within membranes can be directly imaged without labels by using time-of-flight secondary ion mass spectrometry (TOF-SIMS), quantifying the cholesterol abundance at specific membrane locations in a label-free manner remains a challenge. Here, partial least-squares regression (PLSR) of TOF-SIMS data is used to quantitatively measure the local molar percentage (mol %) of cholesterol within supported lipid membranes. With the use of TOF-SIMS data from lipid membranes of known composition, a PLSR model was constructed that correlated the spectral variation to the mol % cholesterol in the membrane. The PLSR model was then used to measure the mol % cholesterol in test membranes and to measure cholesterol exchange between vesicles and supported lipid membranes. The accuracy of these measurements was assessed by comparison to the mol % cholesterol measured with conventional assays. By using this TOF-SIMS/PLSR approach to quantify the mol % cholesterol with location specificity, a better understanding of how the regional lipid composition influences cholesterol abundance and exchange in membranes may be obtained.

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.

Atomic force microscopy: a versatile tool to probe the physical and chemical properties of supported membranes at the nanoscale

Atomic force microscopy (AFM) was developed in the 1980s following the invention of its precursor, scanning tunneling microscopy (STM), earlier in the decade. Several modes of operation have evolved, demonstrating the extreme versatility of this method for measuring the physicochemical properties of samples at the nanoscopic scale. AFM has proved an invaluable technique for visualizing the topographic characteristics of phospholipid monolayers and bilayers, such as roughness, height or laterally segregated domains. Implemented modes such as phase imaging have also provided criteria for discriminating the viscoelastic properties of different supported lipid bilayer (SLB) regions. In this review, we focus on the AFM force spectroscopy (FS) mode, which enables determination of the nanomechanical properties of membrane models. The interpretation of force curves is presented, together with newly emerging techniques that provide complementary information on physicochemical properties that may contribute to our understanding of the structure and function of biomembranes. Since AFM is an imaging technique, some basic indications on how real-time AFM imaging is evolving are also presented at the end of this paper.

Automated correlation and classification of secondary ion mass spectrometry images using a k-means cluster method

We present a novel method for correlating and classifying ion-specific time-of-flight secondary ion mass spectrometry (ToF-SIMS) images within a multispectral dataset by grouping images with similar pixel intensity distributions. Binary centroid images are created by employing a k-means-based custom algorithm. Centroid images are compared to grayscale SIMS images using a newly developed correlation method that assigns the SIMS images to classes that have similar spatial (rather than spectral) patterns. Image features of both large and small spatial extent are identified without the need for image pre-processing, such as normalization or fixed-range mass-binning. A subsequent classification step tracks the class assignment of SIMS images over multiple iterations of increasing n classes per iteration, providing information about groups of images that have similar chemistry. Details are discussed while presenting data acquired with ToF-SIMS on a model sample of laser-printed inks. This approach can lead to the identification of distinct ion-specific chemistries for mass spectral imaging by ToF-SIMS, as well as matrix-assisted laser desorption ionization (MALDI), and desorption electrospray ionization (DESI).

Feasibility of depth profiling of animal tissue by ultrashort pulse laser ablation

Experiments were performed to examine the feasibility of mass spectrometry (MS) depth profiling of animal tissue by ~75 fs, 800 nm laser pulses to expose underlying layers of tissue for subsequent MS analysis. Matrix assisted laser desorption ionization mass spectrometry (MALDI-MS) was used to analyze phospholipids and proteins from both intact bovine eye lens tissue and tissue ablated by ultrashort laser pulses. Laser desorption postionization mass spectrometry (LDPI-MS) with 10.5 eV single photon ionization was also used to analyze cholesterol and other small molecules in the tissue before and after laser ablation. Scanning electron microscopy was applied to examine the ablation patterns in the tissue and estimate the depth of the ablation craters. Ultrashort pulse laser ablation was found to be able to remove a layer of several tens of micrometers from the surface of eye lens tissue while leaving the underlying tissue relatively undamaged for subsequent MS analysis. MS analysis of cholesterol, phospholipids, peptides, and various unidentified species did not reveal any chemical damage caused by ultrashort pulse laser ablation for analytes smaller than ~6 kDa. However, a drop in intensity of larger protein ions was detected by MALDI-MS following laser ablation. An additional advantage was that ablated tissue displayed up to an order of magnitude higher signal intensities than intact tissue when subsequently analyzed by MS. These results support the use of ultrashort pulse laser ablation in combination with MS analysis to permit depth profiling of animal tissue.

Identifying differentiation stage of individual primary hematopoietic cells from mouse bone marrow by multivariate analysis of TOF-secondary ion mass spectrometry data

The ability to self-renew and differentiate into multiple types of blood and immune cells renders hematopoietic stem and progenitor cells (HSPCs) valuable for clinical treatment of hematopoietic pathologies and as models of stem cell differentiation for tissue engineering applications. To study directed hematopoietic stem cell (HSC) differentiation and identify the conditions that recreate the native bone marrow environment, combinatorial biomaterials that exhibit lateral variations in chemical and mechanical properties are employed. New experimental approaches are needed to facilitate correlating cell differentiation stage with location in the culture system. We demonstrate that multivariate analysis of time-of-flight secondary ion mass spectrometry (TOF-SIMS) data can be used to identify the differentiation state of individual hematopoietic cells (HCs) isolated from mouse bone marrow. Here, we identify primary HCs from three distinct stages of B cell lymphopoiesis at the single cell level: HSPCs, common lymphoid progenitors, and mature B cells. The differentiation state of individual HCs in a test set could be identified with a partial least-squares discriminant analysis (PLS-DA) model that was constructed with calibration spectra from HCs of known differentiation status. The lowest error of identification was obtained when the intrapopulation spectral variation between the cells in the calibration and test sets was minimized. This approach complements the traditional methods that are used to identify HC differentiation stage. Further, the ability to gather mass spectrometry data from single HSCs cultured on graded biomaterial substrates may provide significant new insight into how HSPCs respond to extrinsic cues as well as the molecular changes that occur during cell differentiation.

Fluorinated colloidal gold immunolabels for imaging select proteins in parallel with lipids using high-resolution secondary ion mass spectrometry

The local abundance of specific lipid species near a membrane protein is hypothesized to influence the protein's activity. The ability to simultaneously image the distributions of specific protein and lipid species in the cell membrane would facilitate testing these hypotheses. Recent advances in imaging the distribution of cell membrane lipids with mass spectrometry have created the desire for membrane protein probes that can be simultaneously imaged with isotope labeled lipids. Such probes would enable conclusive tests to determine whether specific proteins colocalize with particular lipid species. Here, we describe the development of fluorine-functionalized colloidal gold immunolabels that facilitate the detection and imaging of specific proteins in parallel with lipids in the plasma membrane using high-resolution SIMS performed with a NanoSIMS. First, we developed a method to functionalize colloidal gold nanoparticles with a partially fluorinated mixed monolayer that permitted NanoSIMS detection and rendered the functionalized nanoparticles dispersible in aqueous buffer. Then, to allow for selective protein labeling, we attached the fluorinated colloidal gold nanoparticles to the nonbinding portion of antibodies. By combining these functionalized immunolabels with metabolic incorporation of stable isotopes, we demonstrate that influenza hemagglutinin and cellular lipids can be imaged in parallel using NanoSIMS. These labels enable a general approach to simultaneously imaging specific proteins and lipids with high sensitivity and lateral resolution, which may be used to evaluate predictions of protein colocalization with specific lipid species.